Call Number (LC) Title Results
Q325 .W8 1996 Sheng zhang de xuan lü : Zi zu zhi yan hua de ke xue / 1
Q325.4 Truth from Trash How Learning Makes Sense. 1
Q325.4 .T47 2000 Truth from trash : how learning makes sense / 2
Q325.4 .T47 2000eb Truth from trash : how learning makes sense / 1
Q325.5 Machine learning : a constraint-based approach /
Machine learning : a constraint-based approach.
Applied machine learning and data analytics : 5th International Conference, AMLDA 2022, Reynosa, Tamaulipas, Mexico, December 22-23, 2022, Revised selected papers /
Machine learning for networking : 5th International Conference, MLN 2022, Paris, France, November 28-30, 2022, revised selected papers /
Intelligent systems and machine learning : First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, proceedings.
Machine learning with Python theory and implementation /
Maquina de entrenamiento comprimido basada en Extreme Learning Machine MEC-ELM
Game engines and machine learning /
Learning from multiagent emergent behaviors in a simulated environment /
Deep learning crash course /
Deep learning pipeline : building a deep learning model with TensorFlow /
MACHINE LEARNING APPLICATIONS IN CIVIL ENGINEERING
TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers /
Ensemble methods for machine learning /
Deep reinforcement learning in action.
TensorFlow deep dive : build, train, and deploy machine learning models with TensorFlow.
Grokking deep learning in motion /
Data science and machine learning for non-programmers : using SAS Enterprise Miner /
Machine learning for ios developers.
Scaling TensorFlow using tf.distribute
Machine learning for decision makers : cognitive computing fundamentals for better decision making /
Hands-on machine learning with TensorFlow.js : a guide to building ML applications integrated with web technology using the TensorFlow.js library /
MACHINE LEARNING SECURITY WITH AZURE best practices for assessing, securing, and monitoring Azure Machine Learning workloads /
SYNTHETIC DATA AND GENERATIVE AI
Introduction to ensemble methods /
Deep learning with MXNet cookbook discover an extensive collection of recipes for creating and implementing AI models on MXNet /
Managing machine learning projects /
THE DEFINITIVE GUIDE TO GOOGLE VERTEX AI accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices /
DEVELOPING KAGGLE NOTEBOOKS paving your way to becoming a Kaggle notebooks grandmaster /
Scaling up machine learning : parallel and distributed approaches /
Machine learning and knowledge extraction : 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023, Benevento, Italy, August 29 - September 1, 2023, Proceedings /
Process automation using machine learning /
Sustainable development through machine learning, AI and IoT : first International Conference, ICSD 2023, Delhi, India, July 15-16, 2023, Revised selected papers /
Machine Learning for Sustainable Manufacturing in Industry 4.0 : Concept, Concerns and Applications.
Encyclopedia of machine learning and data mining /
Mastering TensorFlow 1.x : Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras.
Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more /
Practical machine learning for data analysis using python
Machine learning in clinical neuroimaging : 6th international workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, proceedings /
Roadside video data analysis : deep learning /
Advanced analytics and learning on temporal data : 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023 : revised selected papers /
Mastering Machine Learning Algorithms : Expert techniques to implement popular machine learning algorithms and fine-tune your models.
Natural language processing with TensorFlow : teach language to machines using Python's deep learning library /
Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark /
Mathematics and Programming for Machine Learning with R From the Ground Up.
Green Machine Learning Protocols for Future Communication Networks.
Applied machine learning for health and fitness : a practical guide to machine learning with deep vision, sensors, IoT, and VR /
Deep learning for computer vision with SAS : an introduction /
Deep learning with R for beginners : design neural network models in R 3.5 using TensorFlow, Keras, and MXNet /
MATLAB machine learning recipes : a problem-solution approach /
Machine learning in clinical neuroimaging and radiogenomics in neuro-oncology : Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, proceedings /
Applied neural networks with TensorFlow 2 : API oriented deep learning with Python /
Practical machine learning with AWS : process, build, deploy, and productionize your models using AWS /
Practical machine learning in Javascript : tensorflow.js for web developers /
Hyperparameter optimization in machine learning : make your machine learning and deep learning models more efficient /
Beginning MLOps with MLFlow : deploy models in AWS SageMaker, Google Cloud, and Microsoft Azure /
Advanced analytics and learning on temporal data 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised selected papers /
Active inference first international workshop, IWAI 2020, co-located with ECML/PKDD 2020 Ghent, Belgium, September 14, 2020 Proceedings /
Deployable machine learning for security defense first International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings /
Supervised learning with Python : concepts and practical implementation using Python /
Mastering machine learning algorithms : expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work /
Generatives Deep Learning : Maschinen das Malen, Schreiben und Komponieren beibringen /
Machine learning and big data : concepts, algorithms, tools and applications /
Deep Learning - Grundlagen und Implementierung : Neuronale Netze mit Python und PyTorch programmieren /
How automated machine learning empowers businesses /
AI and Machine Learning for Coders.
Deep Learning for Beginners
Machine learning and data mining for sports analytics : 7th International Workshop, MLSA 2020, co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, proceedings /
Transactions on large-scale data- and knowledge-centered systems XLIII
New frontiers in ML-driven customer intelligence /
Can data science help us find what makes a hit television show /
Operationalize ML by empowering people /
Applied machine learning for spreading financial statements /
Leveraging entity-resolution to identify customers in 3rd party data /
Challenges in machine learning from model building to deployment at scale /
Machine learning for cyber physical systems : selected papers from the international conference ML4CPS 2020 /
Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.
Neural structured learning in TensorFlow
Executive briefing : why machine-learned models crash and burn in production and what to do about it /
How Criteo optimized and sped up its TensorFlow models by 10x and served them under 5 ms
Interpretable and resilient AI for financial services /
Using AutoML to automate selection of machine learning models and hyperparameters /
The applied TensorFlow and Keras workshop.
ML at Twitter : a deep dive into Twitter's timeline /
Personalizing the infinite jukebox : ML and the TensorFlow ecosystem at Spotify
TFX : Production ML pipelines with TensorFlow
Getting involved in the TensorFlow community
TensorFlow Lite : Solution for running ML on-device
Build more inclusive TensorFlow pipelines with fairness indicators
Data science isn't just another job /
Executive briefing : usable machine learning - lessons from Stanford and beyond /
Practical feature engineering /
Deep learning projects using TensorFlow 2 : neural network development with Python and Keras /
Automating DevOps for machine learning /
Deep learning for time series data /
Bringing data to life : combining machine learning and art to tell a data story /
The unsupervised learning workshop get started with unsupervised learning and simplify unorganized data to make predictions /
Sooner than you think : neural interfaces are finally here /
Real world machine learning : video edition /
Keras in motion /
Machine learning and knowledge extraction 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25-28, 2020, Proceedings /
Applied machine learning /
Machine learning, image processing, network security and data sciences second International Conference, MIND 2020, Silchar, India, July 30-31, 2020, Proceedings.
Learn Algorithmic Trading : Build and Deploy Algorithmic Trading Systems and Strategies Using Python and Advanced Data Analysis /
Hands-on artificial intelligence on Amazon Web Services : decrease the time to market for AI and ML applications with the power of AWS /
Learn TensorFlow 2.0 : implement machine learning and deep learning models with Python /
Hands-on deep learning with Go : a practical guide to building and implementing neural network models using Go /
Managing machine learning projects : from design to deployment /
Online sentiment : machine learning and prediction /
Deploy machine learning models to production : with Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform /
MACHINE LEARNING AND DEEP LEARNING TECHNIQUES FOR MEDICAL IMAGE RECOGNITION
Intelligent feature selection for machine learning using the dynamic wavelet fingerprint
The development of deep learning technologies research on the development of electronic information engineering technology in China /
Tanmay Teaches Julia for Beginners : A Springboard to Machine Learning for All Ages /
Deep learning for dummies /
Next-Generation Machine Learning with Spark : Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /
Practical MATLAB deep learning : a project-based approach /
The Complete Self-Driving Car Course - Applied Deep Learning
The frontiers of machine learning : 2017 Raymond and Beverly Sackler U.S -U.K. Scientific Forum.
Automated Machine Learning with AutoKeras : Deep Learning Made Accessible for Everyone with Just Few Lines of Coding.
Learning Approaches in Signal Processing /
Applied Supervised Learning with R : Use Machine Learning Libraries of R to Build Models That Solve Business Problems and Predict Future Trends.
Distributed machine learning with Python accelerating model training and serving with distributed systems /
Synthetic data for deep learning : generate synthetic data for decision making and applications with Python and R /
Java deep learning cookbook : train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j /
Machine learning and knowledge discovery in databases European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings.
Design of intelligent applications using machine learning and deep learning techniques /
Graph-powered machine learning / c Alessandro Negro, author.
Graph-powered machine learning /
ECML PKDD 2018 Workshops : Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings /
ICT Innovations 2021 digital transformation : 13th International Conference, ICT Innovations 2021, Virtual event, September 27-28, 2021, Revised selected papers /
Machine learning and metaheuristics algorithms, and applications first symposium, SoMMA 2019, Trivandrum, India, December 18-21, 2019, Revised selected papers /
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, proceedings.
Machine learning and principles and practice of knowledge discovery in databases : international workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022 : proceedings.
Manipulating and Measuring Model Interpretability /
Machine learning systems : designs that scale /
THE REGULARIZATION COOKBOOK explore practical recipes to improve the functionality of your ML models /
Causal inference in Python /
Delivering machine learning projects : from design to deployment /
Sztuczna inteligencja i uczenie maszynowe dla programistów : praktyczny przewodnik po sztucznej inteligencji /
Machine learning for emotion analysis in Python : build AI-powered tools for analyzing emotion using natural language processing and machine learning /
Machine learning for imbalanced data : tackle imbalanced datasets using machine learning and deep learning techniques /
Using federated machine learning to overcome the AI scale disadvantage : a promising new approach to training AI models lets companies with small data sets collaborate while safeguarding proprietary information /
TENSORFLOW DEVELOPER CERTIFICATE GUIDE efficiently tackle deep learning and ML problems to ace the Developer Certificate exam /
Praxiseinstieg Machine Learning mit Scikit-Learn, Keras und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme /
PRACTICAL MACHINE LEARNING ON DATABRICKS seamlessly transition ML models and MLOps on Databricks /
Ji yu Azure de zi dong ji qi xue xi = Practical automated machine learning on Azure /
MACHINE LEARNING INTERVIEWS kickstart your machine learning career and data career /
TinyML cookbook : combine machine learning with microcontrollers to solve real-world problems /
Implementing MLOps in the Enterprise a production-first approach /
Kikai gakushū shisutemu dezain : jitsūn'yō reberu no apurikēshon o jitsugensuru keizokuteki hanpuku purosesu /
Learn Amazon SageMaker : a guide to building, training, and deploying machine learning models for developers and data scientists /
Pretrain Vision and Large Language Models in Python End-To-end Techniques for Building and Deploying Foundation Models on AWS /
Machine Learning : Visuell Lernen von StatQuest : mit Bildern ganz einfach lernen und verstehen /
Jak projektować systemy uczenia maszynowego : iteracyjne tworzenie aplikacji gotowych do pracy /
TinyML : wykorzystanie TensorFlow Lite do uczenia maszynowego na Arduino i innych mikrokontrolerach /
Probablistic machine learning for finance and investing : a primer to generative AI with Python /
A HANDBOOK OF MATHEMATICAL MODELS WITH PYTHON elevate your machine learning projects with Networkx, PuLP, and linalg /
Introduction to MLflow for MLOps.
Learn MLOps for machine learning.
Not with a bug, but with a sticker /
Deep reinforcement learning in action /
AI at the edge : solving real-world problems with embedded machine learning /
Hajimete no TensorFlow.js : JavaScript de manabu kikai gakushū /
What every engineer should know about data-driven analytics /
Serverless machine learning with Amazon Redshift ML : create, train, and deploy machine learning models using familiar SQL commands /
STATISTICS AND MACHINE LEARNING WITH R WORKSHOP unlock the power of efficient data science modeling with this hands-on guide /
Machine learning using R : with time series and industry-based uses in R /
Deep learning patterns and practices /
Privacy-preserving machine learning /
Ji qi xue xi she ji mo shi = Machine learning design patterns /
Jissen kikai gakushū shisutemu /
AZURE MACHINE LEARNING ENGINEERING : deploy, fine -tune and optimize ml models using microsoft azure /
O'Reilly Book Club.
Designing machine learning systems.
AWS Redshift data platform fundamentals.
Hugging Face for MLOps.
AI Superstream.
Practical Java machine learning : projects with Google Cloud platform and Amazon web services /
Cause effect pairs in machine learning /
Pro deep learning with TensorFlow : a mathematical approach to advanced artificial intelligence in Python /
Machine learning in manufacturing : quality 4.0 and the zero defects vision.
MLOps chronicles 11-2021 /
Machine learning and knowledge discovery in databases : Applied data science track : European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings.
Cost-sensitive machine learning
Multi-faceted deep learning models and data /
Machine learning, optimization, and data science 7th International Conference, LOD 2021, Grasmere, UK, October 4-8, 2021, Revised selected papers.
ML.NET revealed : simple tools for applying machine learning to your applications /
Data science solutions on Azure : tools and techniques using Databricks, Azure Synapse, and MLOps /
Machine Learning Theory and Applications : Hands-On Use Cases with Python on Classical and Quantum Machines.
Data science and machine learning : (theory and projects) A to Z.
Deep learning with PyTorch Lightning : build and train high-performance artificial intelligence and self-supervised models using Python /
Implementing machine learning for finance : a systematic approach to predictive risk and performance analysis for investment portfolios /
Deep learning : a visual approach /
Explainable and interpretable models in computer vision and machine learning /
Machine learning and big data analytics paradigms : analysis, applications and challenges /
Applied machine learning using mlr3 in R /
Advances in subsurface data analytics traditional and physics-based machine learning /
MLOps with Hugging Face Spaces, Gradio and Github Actions /
Machine learning in Python : essential techniques for predictive analysis /
Beginning machine learning in the browser : quick-start guide to gait analysis with JavaScript and TensorFlow.js /
Practical machine learning for streaming data with Python : design, develop, and validate online learning models /
Executive briefing : explaining machine learning models /
Fast and lean data science with TPUs.
A framework to bootstrap and scale a machine learning function /
TensorFlow 2.x in the Colaboratory Cloud : an introduction to deep learning on Google's Cloud Service /
Deep learning with Swift for TensorFlow : differentiable programming with Swift /
Optimization and machine learning : optimization for machine learning and machine learning for optimization /
Data Science mit AWS : end-to-end pipelines für continuous machine learning implementieren /
Scikit-learn, Keras, TensorFlow ni yoru jissen kikai gakushū /
Live-coding a machine learning model from scratch /
Machine learning for time series forecasting with Python /
Support vector machines : data analysis, machine learning, and applications /
Thinking machines machine learning and its hardware implementation /
Kernels for structured data /
Federated learning : privacy and incentive /
Introduction to learning classifier systems /
Machine Learning : an algorithmic perspective /
Generative adversarial networks for image-to-image translation /
Machine learning approach for cloud data analytics in IoT /
Machine learning in image steganalysis /
State-of-the-art deep learning models in Tensorflow : modern machine learning in the Google colab ecosystem /
Learning TensorFlow : a guide to building deep learning systems /
Machine learning in image steganalysis
TensorFlow machine learning cookbook : over 60 recipes to build intelligent machine learning systems with the power of Python /
Next-generation sequencing and sequence data analysis /
Hands-on ensemble learning with Python : build highly optimized ensemble machine learning models using scikit-learn and Keras /
Applied probability & statistics : for computer science, data science & machine learning /
Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn /
Deep learning for data analytics : foundations, biomedical applications, and challenges /
Shen du qiang hua xue xi yu GAN ke cheng : shen du xue xi zhong de gao ji zhu ti.
Machine learning methods for behaviour analysis and anomaly detection in video /
Hands-on machine learning with Azure : build powerful models with cognitive machine learning and artificial intelligence /
HANDS-ON MACHINE LEARNING WITH SCIKIT-LEARN, KERAS, AND TENSORFLOW concepts, tools, and techniques to build intelligent systems /
Understanding support vector machines /
Thoughtful machine learning with Python : a test-driven approach /
Machine learning for medical image reconstruction : first International Workshop, MLMIR 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings /
Deploying Spark ML pipelines in production on AWS : how to publish pipeline artifacts and run pipelines in production /
Machine learning in social networks : embedding nodes, edges, communities, and graphs /
MACHINE LEARNING WITH SAP
Machine learning and big data analytics paradigms analysis, applications and challenges /
Computational methods for deep learning : theoretic, practice and applications /
Machine learning, optimization, and data science : 8th International Workshop, LOD 2022, Certosa di Pontignano, Italy, September 19-22, 2022, revised selected papers.
Machine learning for networking third International Conference, MLN 2020, Paris, France, November 24-26, 2020, Revised Selected Papers /
Explainable AI with Python /
Variational methods for machine learning with applications to deep networks
Machine learning and knowledge discovery in databases : applied data science track : European conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.
Machine learning and data mining for emerging trend in cyber dynamics theories and applications /
Machine learning modeling for IoUT networks : internet of underwater things /
Advanced research in technologies, information, innovation and sustainability : first International Conference, ARTIIS 2021, La Libertad, Ecuador, November 25-27, 2021, Proceedings /
Machine learning and knowledge discovery in databases : Research track : European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings.
Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers /
Moving objects detection using machine learning /
Machine learning approaches for convergence of IoT and Blockchain /
Advanced analytics and learning on temporal data : 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised selected papers.
Detecting trust and deception in group interaction
Machine learning and metaheuristics algorithms, and applications second symposium, SoMMA 2020, Chennai, India, October 14-17, 2020, Revised selected papers /
Cyber security meets machine learning
Privacy-preserving deep learning a comprehensive survey /
Advanced deep learning for engineers and scientists a practical approach /
Machine learning in industry
Learning and intelligent optimization : 11th International Conference, LION 11, Nizhny Novgorod, Russia, June 19-21, 2017, Revised selected papers /
Generative adversarial networks projects : build next-generation generative models using TensorFlow and Keras /
Introduction to TensorFlow-Slim : complex TensorFlow model building and training made easy /
Principles and labs for deep learning /
Learning from imbalanced data sets /
Applied supervised learning with R : use machine learning libraries of R to build models that solve business problems and predict future trends /
Applied deep learning with Keras : solve complex real-life problems with the simplicity of Keras /
Machine Learning with Amazon SageMaker Cookbook /
Learn Amazon SageMaker - Second Edition /
Agile machine learning with Datarobot : automate each step of the machine learning life cycle, from preparing data to delivering value /
Beginning deep learning with TensorFlow : work with Keras, MNIST data sets, and advanced neural networks /
Deep learning for human activity recognition : Second International Workshop, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021, proceedings /
Machine learning foundations : supervised, unsupervised, and advanced learning /
Machine Learning and Intelligent Communications : 5th International Conference, MLICOM 2020, Shenzhen, China, September 26-27, 2020 : proceedings /
Machine learning and knowledge extraction : 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual event, August 17-20, 2021, Proceedings /
Control charts and machine learning for anomaly detection in manufacturing /
Machine learning with R
Tree-Based Machine Learning Methods in SAS Viya.
Spotlight on data : the power of deep learning in the hands of domain experts /
Swift for TensorFlow
Strata Data & AI Superstream Series : Deep Learning
ECML PKDD 2020 Workshops : Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): Sogood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings /
Machine learning, optimization, and data science 6th International Conference, LOD 2020, Siena, Italy, July 19-23, 2020, Revised Selected Papers.
Introduction to deep learning and neural networks with Python /
Machine Learning for Time-Series with Python Forecast, Predict, and Detect Anomalies with State-Of-the-art Machine Learning Methods.
Machine learning with TensorFlow /
The deep learning revolution /
Machine learning, optimization, and data science : 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised selected papers /
Machine learning with BigQuery ML create, execute, and improve machine learning models in BigQuery using standard SQL queries /
Machine Learning - kurz & gut Eine Einführung mit Python, Pandas und Scikit-Learn.
Graph machine learning : take graph data to the next level by applying machine learning techniques and algorithms /
The TensorFlow Workshop /
Training a support vector machine in R with mlr.
MLOps talks I want to attend at re:Invent 2021 : /
MLOps for containers with AWS and GCP /
Training a support vector machine in R with mlr,
Exploring the nuances of energy data in Python.
Applied machine learning with BigQuery on Google Cloud /
SageMaker Studio Lab first thoughts : Amazon SageMaker Studio Lab /
Full YOLOv4 pro course bundle /
Interpretable AI or How I learned to stop worrying and trust AI /
Developing classification and regression systems /
All about TensorFlow and the cool things that NASA is doing with it.
Building effective data science infrastructure in 30 minutes /
Kicking the tires on MLOps framework MLRun /
MLOps maturity model /
Doing MLOps live talk and demo /
Advantages of graph-based machine learning systems /
Playing with GANs : building, coding, and modifying deep learning GAN models.
Ji qi xue xi he AI jing cui.
Efficient machine learning /
Getting started with time series forecasting in Python.
Distributed machine learning and gradient optimization
MACHINE LEARNING ENGINEERING ON AWS building, scaling, and securing machine learning systems and MLOps pipelines in production /
Advances in machine learning and data science : recent achievements and research directives /
The complete PyTorch course : deep learning & computer vision.
Machine learning methods for planning /
Machine learning on Kubernetes : a practical handbook for building and using a complete open source machine learning platform on Kubernetes /
Feature Store for Machine Learning Curate, Discover, Share and Serve ML Features at Scale.
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings.
TinyML : li yu TensorFlow Lite zai Arduino he chao di gong hao wei kong zhi qi shang bu shu ji qi xue xi = TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers /
Ji qi xue xi liu shui xian shi zhan = Building machine learning pipelines /
Shen du xue xi : nei hang ren de zuo fa = Deep learning : a practitioner's approach /
Network Intrusion Detection using Deep Learning : a Feature Learning Approach /
Machine learning : a practical approach on the statistical learning theory /
Machine learning and knowledge extraction : second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Hamburg, Germany, August 27-30, 2018, Proceedings /
Tensorflow for dummies /
Multiview machine learning /
Machine learning for the quantified self : on the art of learning from sensory data /
The development of deep learning technologies : research on the development of electronic information engineering technology in China /
Agile machine learning : effective machine learning inspired by the agile manifesto /
TensorFlow 2.0 pocket primer /
Machine learning for iOS developers /
Deep learning in mining of visual content /
Real-world machine learning /
Machine learning using R /
MATLAB machine learning /
Accelerated optimization for machine learning first-order algorithms /
Financial signal processing and machine learning /
Machine learning and data mining for sports analytics 8th International Workshop, MLSA 2021, Virtual event, September 13, 2021, revised selected papers /
Information fusion machine learning methods /
MLOps masterclass : theory to DevOps to Cloud-native to AutoML /
Machine learning for text /
Machine learning and intelligent communications : 6th EAI International Conference, MLICOM 2021, virtual event, November 2021 : proceedings /
Designing Machine Learning Systems
Managing data science : effective strategies to manage data science projects and build a sustainable team /
Conda commands for beginners.
52 weeks of AWS,
Zero to MLOps with Databricks on Azure course.
Machine learning for dummies /
Practical machine learning with Python : a problem-solver's guide to building real-world intelligent systems /
Pro machine learning algorithms : a hands-on approach to implementing algorithms in Python and R /
Applied deep learning : a case-based approach to understanding deep neural networks /
Industrial applications of machine learning /
Machine learning and non-volatile memories
Granular computing based machine learning : a big data processing approach /
Machine learning, optimization, and big data : third International Conference, MOD 2017, Volterra, Italy, September 14-17, 2017, Revised selected papers /
The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) /
Probabilistic deep learning : with Python, Keras, and TensorFlow Probability /
Data science solutions with Python : fast and scalable models using Keras, Pyspark Mllib, H2O, XGBoost, and scikit-Learn /
Practical Simulations for Machine Learning
Abstract state machines, Alloy, B, TLA, VDM, and Z : 6th International Conference, ABZ 2018, Southampton, UK, June 5-8, 2018, Proceedings /
Kikai gakushū ni yoru jitsuyō apurikēshon kōchiku : jirei o tsūjite manabu, sekkei kara honban kadō made no purosesu /
Python de hajimeru kyōshi nashi gakushū : kikai gakushū no kanōsei o hirogeru raberu nashi dēta no riyō /
Machine learning bookcamp /
Edge analytics : select proceedings of 26th International Conference -- ADCOM 2020 /
Ransomware /
Machine learning engineering in action /
MLOps Engineering at Scale
End-to-end machine learning : from training a model to deploying to the cloud.
The essential machine learning foundations : math, probability, statistics, and computer science (Video Collection)
Shu ju fen xi yu ji qi xue xi ji chu.
Machine learning and artificial intelligence with industrial applications : from big data to small data /
Chu tan shen du xue xi : shi yong TensorFlow = TensorFlow for deep learning : from linear regression to reinforcement learning /
Advanced model deployments with TensorFlow serving /
Working with TensorFlow Lite on Android with C++ /
Recommending art with feature engineering /
Generative malware outbreak detection /
TensorFlow model optimization : quantization and pruning /
Intelligent Data Analytics, IoT, and Blockchain
Nyūmon kikai gakushū paipurain : TensorFlow de manabu wāku furō no jidōka /
Hands-On Gradient Boosting with XGBoost and scikit-learn : Perform accessible machine learning and extreme gradient boosting with Python. /
Federated learning for wireless networks
Automated machine learning and meta-learning for multimedia
Machine learning avec Scikit-Learn : mise en œuvre et cas concrets /
TensorFlow 2 Reinforcement Learning Cookbook Over 50 Recipes to Help You Build, Train, and Deploy Learning Agents for Real-World Applications.
Language Models in Plain English
Engineering MLOps Rapidly Build, Test, and Manage Production-Ready Machine Learning Life Cycles at Scale.
Metalearning : applications to automated machine learning and data mining /
Machine learning with R quick start guide : a beginner's guide to implementing machine learning techniques from scratch using R 3.5 /
MemComputing : fundamentals and applications /
Accelerate machine learning with a unified analytics architecture : deploy machine learning models in minutes, not months /
Kubeflow for machine learning : from lab to production /
MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS.
Getting started with Amazon SageMaker Studio : learn to build end-to-end machine learning projects in the SageMaker machine learning IDE /
TinyML Cookbook Combine Artificial Intelligence and Ultra-Low-power Embedded Devices to Make the World Smarter.
Using lightning and hangar with PyTorch to reduce coding in deep learning projects.
Hands-on machine learning for algorithmic trading bots with Python.
Oracle business intelligence with machine learning : artificial intelligence techniques in OBIEE for actionable BI /
Implementing machine learning with SAP S/4HANA /
Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum data /
Beginning deep learning with TensorFlow work with Keras, MNIST data sets, and advanced neural networks /
Learning systems : from theory to practice /
Machine learning for model order reduction /
On the learnability of physically unclonable functions /
TensorFlow shen du xue xi ke cheng : shen du shen jing wang luo zai ji qi xue ren wu de ying yong.
Intelligent systems proceedings of ICMIB 2021 /
Kernel methods for machine learning with Math and R 100 exercises for building logic /
Braverman readings in machine learning : key ideas from inception to current state : International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, invited talks /
Mastering Azure machine learning : execute large-scale end-to-end machine learning with Azure /
Practical Deep Learning at Scale with MLflow Bridge the Gap Between Offline Experimentation and Online Production /
Practical machine learning for data analysis using python /
MLOps packaging : HuggingFace and Docker.
Learning Apache Mahout : acquire practical skills in Big Data Analytics and explore data science with Apache Mahout /
Python machine learning bootcamp.
Machine learning, image processing, network security and data sciences : 4th International Conference, MIND 2022, Virtual event, January 19-20, 2023, Proceedings.
Machine learning, image processing, network security and data sciences : 4th International Conference, MIND 2022, Virtual Event, January 19-20, 2023, Proceedings.
AI and machine learning for coders : a programmer's guide to artificial intelligence /
Deep learning and XAI techniques for anomaly detection : integrating the theory and practice of deep anomaly explainability /
APPLIED MACHINE LEARNING FOR HEALTHCARE AND LIFE SCIENCES USING AWS transformational AI implementations for biotech, clinical, and healtcare organizations /
Machine learning and knowledge discovery in databases : Applied data science and demo track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.
Machine learning and knowledge discovery in databases : Research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.
Machine learning and knowledge discovery in databases : research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.
Learning and intelligent optimization : 16th International Conference, LION 16, Milos Island, Greece, June 5-10, 2022, revised selected papers /
Machine learning for cyber security : 4th International Conference, ML4CS 2022, Guangzhou, China, December 2-4, 2022, proceedings.
Proceedings of the 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications : ICMISC 2022 /
Proceedings of International Conference on Frontiers in Computing and Systems COMSYS 2021 /
Machine learning and principles and practice of knowledge discovery in databases : International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, proceedings.
Representation in machine learning /
Machine learning and data mining for sports analytics : 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised selected papers /
Machine learning empowered intelligent data center networking : evolution, challenges and opportunities /
Machine learning in information and communication technology : proceedings of ICICT 2021, SMIT /
Federated learning fundamentals and advances /
Grokking machine learning /
AI at the edge solving real-world problems with embedded machine learning /
Towards a Theory for Designing Machine Learning Systems for Complex Decision Making Problems.
Introduction to Unity ML-Agents : understand the interplay of neural networks and simulation space using the Unity ML-Agents Package /
Computational intelligence and smart communication : first international conference, ICCISC 2022, Dehradun, India, June 10-11, 2022 : revised selected papers /
Computational methods for deep learning : theory, algorithms, and implementations /
Neuro symbolic reasoning and learning /
Machine learning : concepts, techniques and applications /
Machine learning and knowledge discovery in databases : Applied data science and Demo track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.
Evolutionary approach to machine learning and deep neural networks : neuro-evolution and gene regulatory networks /
Building Recommender systems with machine learning and AI /
Python reinforcement learning projects : eight hands-on projects exploring reinforcement learning algorithms using TensorFlow /
Evaluating machine learning models : a beginner's guide to key concepts and pitfalls /
Data science algorithms in a week : top 7 algorithms for scientific computing, data analysis, and machine learning /
Beginning data science with Python and Jupyter /
Security superstream : zero trust /
TensorFlow in action /
Interpretable AI : building explainable machine learning systems /
Machine learning for developers : uplift your regular applications with the power of statistics, analytics, and machine learning /
Scikit-learn cookbook : over 80 recipes for machine learning in Python with scikit-learn /
Neural network programming with TensorFlow : unleash the power of TensorFlow to train efficient neural networks /
Leveraging multi-CDN at Riot Games /
Machine learning with TensorFlow 1.x : second generation machine learning with Google's brainchild - TensorFlow 1.x /
Scikit-learn : machine learning simplified.
Deploying machine learning models as microservices using Docker : a REST-based architecture for serving ML model outputs at scale /
Training and exporting machine learning models in Spark : a hands-on guide to train, score, evaluate, and export machine learning models /
Monitoring and improving the performance of machine learning models : how to use ModelDB and Spark to track and improve model performance over time /
An introduction to machine learning models in production : how to transition from one-off models to reproducible pipelines /
TensorFlow 1.x deep learning cookbook : over 90 unique recipes to solve artificial-intelligence driven problems with Python /
Mastering TensorFlow 1.x : advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras /
Feature engineering made easy : identify unique features from your dataset in order to build powerful machine learning systems /
An introduction to machine learning interpretability : an applied perspective on fairness, accountability, transparency, and explainable AI /
TensorFlow for deep learning : from linear regression to reinforcement learning /
TensorFlow for dummies /
TensorFlow deep learning projects : 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning /
HYPERPARAMETER TUNING WITH PYTHON boost your machine learning model's performance via hyperparameter tuning.
Machine learning for adaptive many-core machines -- a practical approach /
Grokking Machine Learning, video edition /
Enterprise MLOps Interviews.
Comet for data science : enhance your ability to manage and optimize the life cycle of your data science project /
The Kaggle book : data analysis and machine learning for competitive data science /
Feature engineering bookcamp /
PRODUCTION-READY APPLIED DEEP LEARNING learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks /
Fundamentals and methods of machine and deep learning : algorithms, tools and applications /
Sentiment analysis with LSTMs and mitigating class imbalance in TensorFlow.
Machine learning in clinical neuroimaging : 5th international workshop, MLCN 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings /
Machine Learning with scikit-learn quick start guide : classification, regression, and clustering techniques in Python /
Real world active learning : applications and strategies for human-in-the-loop machine learning /
Machine learning logistics : model management in the real world /
Serving machine learning models : a guide to architecture, stream processing engines, and frameworks /
Considering TensorFlow for the enterprise : an overview of the deep learning ecosystem /
Artificial intelligence and machine learning fundamentals /
Beginning machine learning in iOS : CoreML framework /
Machine learning fundamentals /
Machine learning in production : developing and optimizing data science workflows and applications /
R machine learning projects : implement supervised, unsupervised, and reinforcement learning techniques using R 3.5 /
Feature engineering for machine learning : principles and techniques for data scientists /
Deep learning cookbook : practical recipes to get started quickly /
Security with AI and machine learning : using advanced tools to improve application security at the edge /
Machine learning quick reference : quick and essential machine learning hacks for training smart data models /
Beginning machine learning with AWS /
Mastering machine learning with R : advanced machine learning techniques for building smart applications with R 3.5 /
Python machine learning blueprints : put your machine learning concepts to the test by developing real-world smart projects /
Bringing machine learning to software-defined networks /
EXPLAINABLE AI FOR PRACTITIONERS designing and implementing explainable ML solutions /
Security superstream : security in the cloud.
Learning and intelligent optimization : 12th International Conference, LION 12, Kalamata, Greece, June 10-15, 2018, Revised selected papers /
FEDERATED LEARNING WITH PYTHON design and implement a federated learning system and develop applications using existing frameworks /
Deep learning through sparse and low-rank modeling /
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings.
Test-driven machine learning : control your machine learning algorithms using test-driven development to achieve quantifiable milestones /
R machine learning by example : understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully /
Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models /
Learn Unity ML-Agents : fundamentals of Unity machine learning : incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games /
Machine learning for computer scientists and data analysts : from an applied perspective /
Deep learning for numerical applications with SAS /
Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras /
Machine learning algorithms : popular algorithms for data science and machine learning /
Microsoft Azure machine learning : explore predictive analytics using step-by-step tutorials and build models to make prediction in a jiffy with a few mouse clicks /
Machine learning projects for .NET developers /
Advanced machine learning with scikit-learn : tools and techniques for predictive analytics in Python /
Training, evaluating, and tuning deep neural network models with TensorFlow-Slim : advanced topics in training, evaluating, and tuning deep neural network models /
Mastering machine learning with R : advanced prediction, algorithms, and learning methods with R 3.x /
Effective Amazon machine learning : machine learning in the Cloud /
Introduction to deep learning models with TensorFlow : learn how to work with TensorFlow to create and run a TensorFlow graph, and build a deep learning model /
Machine learning with Spark : develop intelligent machine learning systems with Spark 2.x /
Introduction to computer vision with TensorFlow : using convolutional neural networks and TensorFlow to solve computer vision tasks /
Machine learning for designers : an introduction to the core technologies of machine learning and the emerging opportunities for ML-enhanced design /
R : unleash machine learning techniques : find out how to build smarter machine learning systems with R : follow this three module course to become a more fluent machine learning practitioner : a course in three modules.
ACCELERATE DEEP LEARNING WORKLOADS WITH AMAZON SAGEMAKER train, deploy and scale deep learning models effectively using Amazon Sagemaker /
Intelligent Document Processing with AWS AI/ML A Comprehensive Guide to Building IDP Pipelines with Applications Across Industries /
Machine learning and data mining for sports analytics : 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings /
Deep learning with R /
Deep learning with TensorFlow and Keras /
The machine learning solutions architect handbook : create machine learning platforms to run solutions in an enterprise setting /
Applied machine learning and AI for engineers : solve business problems that can't be solved algorithmically /
Machine learning for time series data analysis.
Learning from data streams in evolving environments : methods and applications /
Applying machine learning for automated classification of biomedical data in subject-independent settings /
Practical Automated Machine Learning Using H2O.ai Discover the Power of Automated Machine Learning, from Experimentation Through to Deployment to Production /
Python for machine learning : the complete beginner's course.
Federated learning over wireless edge networks /
Scaling data analysis with Apache Mahout /
Machine learning for dynamic software analysis : potentials and limits : International Dagstuhl Seminar 16172, Dagstuhl Castle, Germany, April 24-27, 2016, Revised papers /
STOCHASTIC OPTIMIZATION FOR LARGE-SCALE MACHINE LEARNING.
MLOps key concepts.
Machine learning and knowledge extraction : 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, Vienna, Austria, August 23-26, 2022, proceedings /
Cutting edge MLOps from zero with Hugging Face and OpenAI.
Assimilate Google machine learning certification.
RELIABLE MACHINE LEARNING applying SRE principles to ML in production /
Proceedings of the second annual Workshop on Computational Learning Theory : University of California, Santa Cruz, July 31- August 2, 1989 /
Machine learning : a Bayesian and optimization perspective /
Ji qi xue xi : gong zuo xian chang de ping gu, dao ru yu shi zuo = Deep learning /
TensorFlow.js model training.
Machine Learning for Streaming Data with Python Rapidly Build Practical Online Machine Learning Solutions Using River and Other Top Key Frameworks /
Hello, TensorFlow! : building and training your first TensorFlow graph from the ground up /
Dynamic fuzzy machine learning /
What developers need to know to design machine learning systems.
MLOps packaging : HuggingFace and GitHub container registry /
Doing hugging face : Pragmatic AI Labs course.
Gradient boosting from scratch.
Machine learning for the web : explore the web and make smarter predictions using Python /
Apache Spark machine learning blueprints : develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide /
Machine learning for designers /
Large scale machine learning with python : learn to build powerful machine learning models quickly and deploy large-scale predictive applications /
Dealing with real-world data.
Supervised classification algorithms.
Mastering machine learning with Spark 2.x : create scalable machine learning applications to power a modern data-driven business using Spark /
Clustering and unsupervised learning.
Machine learning using R : a comprehensive guide to machine learning /
AI and deep learning for NLP : tools and techniques for the enterprise.
Apache Spark 2.x machine learning cookbook : over 100 recipes to simplify machine learning model implementations with Spark /
Automated machine learning in action : AutoML basics.
Machine Learning at Scale with H2O A Practical Guide to Building and Deploying Machine Learning Models on Enterprise Systems /
Applied Machine Learning Explainability Techniques Make ML Models Explainable and Trustworthy for Practical Applications Using LIME, SHAP, and More /
Machine learning and security : protecting systems with data and algorithms /
Machine learning for absolute beginners /
R deep learning projects : master the techniques to design and develop neural network models in R /
Deep reinforcement learning and GANS Livelessons /
Neural networks and deep learning /
Getting started with deep learning /
Machine learning with Python cookbook : practical solutions from preprocessing to deep learning /
Machine learning : algorithms and applications /
Exam ref 70-774 perform cloud data science with Azure machine learning /
Hands-on machine learning on Google cloud platform : implementing smart and efficient analytics using Cloud ML Engine /
Introduction to deep learning business applications for developers : from conversational bots in customer service to medical image processing /
The evolution of analytics : opportunities and challenges for machine learning in business /
The path to predictive analytics and machine learning /
Intelligent mobile projects with TensorFlow : build 10+ artificial intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi /
The future of machine intelligence : perspectives from leading practitioners /
Hands-on data science with Anaconda : utilize the right mix of tools to create high-performance data science applications /
Machine learning is changing the rules : ways business can utilize AI to innovate /
Federated learning : a comprehensive overview of methods and applications /
Machine learning with Core ML : an iOS developer's guide to implementing machine learning in mobile apps /
Practical machine learning with H2O : powerful, scalable techniques for deep learning and AI /
Introduction to Amazon machine learning : learn how to build data driven predictive applications with Amazon Web Services (AWS) /
Deep learning with TensorFlow /
Machine learning algorithms : reference guide for popular algorithms for data science and machine learning /
Hands-on deep learning with TensorFlow : uncover what is underneath your data! /
THE KAGGLE WORKBOOK self-learning exercises and valuable insights for Kaggle data science competitions /
Machine learning for cybersecurity : innovative deep learning solutions /
Adversarial robustness for machine learning models
Hands-on deep learning with Apache Spark : build and deploy distributed deep learning applications on Apache Spark /
Grokking deep learning /
Deep learning and the game of Go /
Assimilate PyTorch.
No-code machine learning using Amazon AWS SageMaker Canvas.
ECML PKDD 2018 workshops : DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised selected papers /
Machine learning security principles : use various methods to keep data, networks, users, and applications safe from prying eyes /
Pro deep learning with TensorFlow 2.0 : a mathematical approach to advanced artificial intelligence in Python /
PRACTICING TRUSTWORTHY MACHINE LEARNING : consistent, transparent, and fair ai pipelines.
Machine learning : random forest with Python from scratch.
Machine learning in Python for everyone.
AI and machine learning for on-device development : a programmer's guide /
Improving classifier generalization : real-time machine learning based applications /
A pragmatic programmer for machine learning : engineering analytics and data science solutions /
Hamiltonian Monte Carlo methods in machine learning /
Machine learning and knowledge discovery in databases : applied data science and demo track : European conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.
Deep sciences for computing and communications : first International Conference, IconDeepCom 2022, Chennai, India, March 17-18, 2022, Revised selected papers /
Trustworthy federated learning : first International Workshop, FL 2022, held in conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised selected papers /
Kikai gakushū dezain patān : dēta junbi, moderu kōchiku, MLOps no jissenjō no mondai to kaiketsu /
Not with a Bug, but with a Sticker Attacks on Machine Learning Systems and What to Do about Them.
Post-shrinkage strategies in statistical and machine learning for high dimensional data /
Applied data science with Python and Jupyter /
Shigoto de hajimeru kikai gakushū /
Ugokashite manabu AI, kikai gakushū no kiso : TensorFlow ni yoru konpyūta bijon, shizen gengo shori, jikeiretsu dēta no yosoku to depuroi /
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings.
Deep learning.
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2022, Grenoble, France, September, 19-23, 2022, proceedings.
Automated machine learning : methods, systems, challenges /
Machine learning for networking : first International Conference, MLN 2018, Paris, France, November 27-29, 2018, Revised selected papers /
Einführung in Machine Learning mit Python : Praxiswissen Data Science /
Praxiseinstieg Machine Learning mit Scikit-Learn und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme /
Introduction to algorithms for data mining and machine learning /
Machine learning theory and applications /
Learning and reasoning in hybrid structured spaces /
Generative deep learning : teaching machines to paint, write, compose, and play /
An introduction to machine learning /
Machine Learning Kochbuch : Praktische Lösungen mit Python: von der Vorverarbeitung der Daten bis zum Deep Learning /
Machine learning algorithms in 7 days /
Merkmalskonstruktion für Machine Learning : Prinzipien und Techniken der Datenaufbereitung /
Amazon machine learning /
Deep learning Kochbuch : Praxisrezepte für einen schnellen Einstieg /
Einführung in TensorFlow : Deep-Learning-Systeme programmieren, trainieren, skalieren und deployen /
Machine learning : kurz & gut /
Hands-on neural networks with Keras : design and create neural networks using deep learning and artificial intelligence principles /
Deep learning : das umfassende Handbuch : Grundlagen, aktuelle Verfahren und Algorithmen, neue Forschungsansätze /
Machine learning and artificial intelligence
Algorithms in machine learning paradigms /
Machine learning, optimization, and big data : first International Workshop, MOD 2015, Taormina, Sicily, Italy, July 21-23, 2015, Revised selected papers /
Machine learning for networking Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3-5, 2019, Revised selected papers /
Unsupervised learning in space and time a modern approach for computer vision using graph-based techniques and deep neural networks /
Deep learning techniques for biomedical and health informatics
Machine learning and knowledge discovery in databases International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings.
Implementations and applications of machine learning
Machine learning approaches to non-intrusive load monitoring /
Machine learning for medical image reconstruction : second International Workshop, MLMIR 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /
Hybrid machine intelligence for medical image analysis /
Supervised and unsupervised learning for data science
Domain Adaptation Theory Available Theoretical Results.
Machine learning for signal processing : data science, algorithms, and computational statistics /
Fundamentals of machine learning /
Machine Learning, Optimization, and Data Science 5th International Conference, LOD 2019, Siena, Italy, September 10-13, 2019, Proceedings /
Machine learning with PyTorch /
Introduction to statistical machine learning /
Practical automated machine learning on Azure : using Azure machine learning to quickly build AI solutions /
Practical time series analysis : prediction with statistics and machine learning /
Programming PyTorch for deep learning : creating and deploying deep learning applications /
Machine learning with scikit-learn : LiveLessons /
Hands-on generative adversarial networks with Keras : your guide to implementing next-generation generative adversarial networks /
Machine learning for cyber security : second International Conference, ML4CS 2019, Xi'an, China, September 19-21, 2019, Proceedings /
Turning data into insight with IBM Machine Learning for z/OS /
Machine Learning kompakt : Alles, was Sie wissen müssen /
Deep learning illustrated : a visual, interactive guide to artificial intelligence /
Keras to Kubernetes : the journey of a machine learning model to production /
Machine learning at enterprise scale : how real practitioners handle six common challenges /
Assimilate ONNX : portable models /
Assimilate TensorFlow with Rust /
Explainable deep learning AI : methods and challenges /
Cost-sensitive machine learning /
Deep learning and parallel computing environment for bioengineering
Deep learning and convolutional neural networks for medical imaging and clinical informatics /
Hands-on machine learning with Microsoft Excel 2019 build complete data analysis flows, from data collection to visualization /
ADVANCES IN COMPLEX DECISION MAKING using machine learning and tools for service-oriented computing /
Alternating direction method of multipliers for machine learning
Data analytics and machine learning fundamentals : LiveLessons /
Deep learning receptury /
Intelligent data-analytics for condition monitoring smart grid applications /
Machine learning and data monetization /
Handbook of research on machine learning : foundations and applications /
MACHINE LEARNING USING TENSORFLOW COOKBOOK : over 60 recipes on machine learning using deep ... learning solutions from kaggle masters and google.
Machine learning : modern computer vision & generative AI.
Math 0-1 : matrix calculus in data science and machine learning.
The art of machine learning : a hands-on guide to machine learning with R /
Deep learning for data analytics foundations, biomedical applications, and challenges /
PyTorch deep learning in 7 days /
Hybrid classifiers : methods of data, knowledge, and classifier combination /
Machine learning meets medical imaging : first International Workshop, MLMMI 2015, held in conjunction with ICML 2015, Lille, France, July 11, 2015, Revised selected papers /
Human activity recognition and prediction
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings.
Analysis and design of machine learning techniques : evolutionary solutions for regression, prediction, and control problems /
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings.
Machine learning in healthcare informatics /
Measures of complexity : festschrift for Alexey Chervonenkis /
Abstract state machines, Alloy, B, TLA, VDM, and Z : 4th International Conference, ABZ 2014, Toulouse, France, June 2-6, 2014. Proceedings /
Advanced machine learning technologies and applications : second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings /
Machine learning for cyber physical systems : selected papers from the International Conference ML4CPS 2015 /
Twin support vector machines : models, extensions and applications /
Support vector machines applications /
Soft computing in machine learning /
Machine learning in complex networks /
Computational learning theory 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, the Netherlands, July 16-19, 2001 : proceedings /
Advanced machine learning /
Machine learning in action /
Computational learning theory 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8-10, 2002 : proceedings /
Learning to Learn /
Reverse hypothesis machine learning : practitioner's perspective /
Knowledge transfer between computer vision and text mining : similarity-based learning approaches /
Learning theory and Kernel machines 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003 : proceedings /
Advances in machine learning and signal processing : proceedings of MALSIP 2015 /
Machine learning for cyber physical systems : selected papers from the International Conference ML4CPS 2016 /
Conformal and probabilistic prediction with applications : 5th International Symposium, COPA 2016, Madrid, Spain, April 20-22, 2016, Proceedings /
Machine learning 101 with Scikit-Learn and StatsModels /
Deep learning with structured data
Machine learning and intelligent communication : 7th EAI International Conference, MLICOM 2022, Virtual event, October 23-24, 2022 : proceedings /
Deep learning on Windows : building deep learning computer vision systems on Microsoft Windows /
Machine learning and cognition in enterprises : business intelligence transformed /
Privacy-Preserving Machine Learning
Synthetic data for machine learning revolutionize your approach to machine learning with this comprehensive conceptual guide /
Mathe-Basics für Data Scientists : lineare Algebra, Statistik und Wahrscheinlichkeitsrechnung für die Datenanalyse /
Challenges in machine generation of analytic products from multi-source data : proceedings of a workshop /
Getting started with machine learning in the cloud : using cloud-based platforms to discover new business insights /
Applications of machine learning
Abstract state machines, Alloy, B, TLA, VDM, and Z : 5th International Conference, ABZ 2016, Linz, Austria, May 23-27, 2016, Proceedings /
Topics in grammatical inference /
Machine intelligence and signal processing /
Machine learning for evolution strategies /
Machine learning and intelligent communications : first International Conference, MLICOM 2016, Shanghai, China, August 27-28, 2016, Revised Selected Papers /
Machine intelligence and big data in industry /
Machine learning techniques for gait biometric recognition : using the ground reaction force /
Learning and intelligent optimization : 8th International Conference, Lion 8, Gainesville, FL, USA, February 16-21, 2014. Revised selected papers /
Unsupervised learning algorithms /
Planning and learning by analogical reasoning /
Five-layer intelligence of the machine brain system modelling and simulation /
Machine intelligence and data science applications proceedings of MIDAS 2021 /
Recommender systems in fashion and retail /
Information management and machine intelligence proceedings of ICIMMI 2019 /
Deep learning : algorithms and applications /
Black box optimization, machine learning, and no-free lunch theorems
Cellular learning automata theory and applications /
Machine intelligence and signal analysis /
Supervised learning with Python concepts and practical implementation using Python /
Machine learning and big data analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)
Learn TensorFlow 2.0 implement machine learning and deep learning models with Python /
Representation learning propositionalization and embeddings /
Machine learning and computational intelligence techniques for data engineering : Proceedings of the 4th International Conference MISP 2022.
Advances in machine learning for big data analysis
Practical machine learning in Javascript tensorflow.js for web developers /
Deep learning architectures a mathematical approach /
Intelligent systems : proceedings of ICMIB 2020 /
Machine learning paradigms : applications of learning and analytics in intelligent systems /
Model selection and error estimation in a nutshell /
Machine Learning with the Raspberry Pi Experiments with Data and Computer Vision /
Deep learning applications.
Innovations in machine and deep learning : case studies and applications /
Generative adversarial learning architectures and applications /
Machine learning meets quantum physics
Learning and intelligent optimization : 13th International Conference, LION 13, Chania, Crete, Greece, May 27-31, 2019, revised selected papers /
Intelligent systems and applications Proceedings of the 2020 Intelligent Systems Conference (IntelliSys).
Machine learning for practical decision making a multidisciplinary perspective with applications from healthcare, engineering and business analytics /
Machine learning and big data analytics : 2nd International Conference on Machine Learning and Big Data Analytics-ICMLBDA, IIT Patna, India, March 2022 /
Applied machine learning for health and fitness a practical guide to machine learning with deep vision, sensors, IoT, and VR /
Fusion of machine learning paradigms : theory and applications /
Development and analysis of deep learning architectures /
Deep learning projects using TensorFlow 2 neural network development with Python and Keras /
Data science solutions on Azure tools and techniques using Databricks, Azure Synapse, and MLOps /
Game-theoretic learning and distributed optimization in memoryless multi-agent systems
Deep learners and deep learner descriptors for medical applications
Machine learning for cyber physical systems : selected papers from the International Conference ML4CPS 2017 /
Optimization in Machine Learning and Applications
Machine learning for intelligent multimedia analytics : techniques and applications /
Machine learning in medicine-- Cookbook /
Machine learning and information processing proceedings of ICMLIP 2020 /
Proceedings of International Conference on Big Data, Machine Learning and their Applications : ICBMA 2019 /
Proceedings of International Conference on Machine Intelligence and Data Science Applications : MIDAS 2020 /
Practical MATLAB deep learning a project-based approach /
Application of FPGA to real-time machine learning : hardware reservoir computers and software image processing /
Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications ICMISC 2021 /
Advances in artificial systems for logistics engineering
Interdisciplinary evolution of the machine brain : vision, touch & mind /
Machine learning, deep learning and computational intelligence for wireless communication : proceedings of MDCWC 2020 /
ML.NET revealed simple tools for applying machine learning to your applications /
Machine learning and autonomous systems proceedings of ICMLAS 2021 /
A machine learning based pairs trading investment strategy
Minimum divergence methods in statistical machine learning from an information geometric viewpoint /
Computational intelligence in recent communication networks
Targeted learning in data science : causal inference for complex longitudinal studies /
Deep learning techniques for IoT security and privacy
Internet of Things, smart computing and technology a roadmap ahead /
Deep learning in data analytics recent techniques, practices and applications /
Agile machine learning effective machine learning inspired by the agile manifesto /
Learning and intelligent optimization 14th International Conference, LION 14, Athens, Greece, May 24-28, 2020, Revised selected papers /
Proceedings of Integrated Intelligence Enable Networks and Computing : IIENC 2020 /
Machine learning algorithms adversarial robustness in signal processing /
Recent developments in machine learning and data analytics : IC3 2018 /
Advanced machine intelligence and signal processing /
Enabling machine learning applications in data science proceedings of Arab Conference for Emerging Technologies 2020 /
Deep learning applications
Understanding the impact of machine learning on labor and education : a time-dependent Turing test /
Inductive biases in machine learning for robotics and control /
Deploy machine learning models to production with Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform /
Next-Generation Machine Learning with Spark Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /
Machine intelligence techniques for data analysis and signal processing : proceedings of the 4th International Conference MISP 2022.
A few things I know about her : a personally machine learning inspired approach to understand surrounding nature /
Machine learning algorithms for industrial applications
State-of-the-art deep learning models in Tensorflow modern machine learning in the Google colab ecosystem /
Modern approaches in machine learning and cognitive science : a walkthrough : latest trends in AI.
Multi-aspect learning : methods and applications /
Feature learning and understanding algorithms and applications /
Implementing machine learning for finance a systematic approach to predictive risk and performance analysis for investment portfolios /
Machine learning with quantum computers /
Proceedings of Second International Conference on Advances in Computer Engineering and Communication Systems : ICACECS 2021 /
Modern approaches in machine learning & cognitive science a walkthrough /
Advanced machine learning technologies and applications proceedings of AMLTA 2020 /
Proceedings of International Conference on Frontiers in Computing and Systems : COMSYS 2020 /
Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications ICMISC 2020 /
Machine learning for intelligent decision science
Machine learning and information processing proceedings of ICMLIP 2019 /
Fashion recommender systems
Machine learning-based natural scene recognition for mobile robot localization in an unknown environment
Classification applications with deep learning and machine learning technologies
Machine learning technologies and applications Proceedings of ICACECS 2020 /
Machine learning for cyber agents attack and defence /
Deep learning pipeline building a deep learning model with TensorFlow /
Machine learning for robotics applications /
Generative adversarial networks for image generation /
Machine learning and data analytics for solving business problems methods, applications, and case studies /
Machine learning using R
Machine learning : theoretical foundations and practical applications /
Machine learning paradigms advances in deep learning-based technological applications /
Machine learning in modeling and simulation : methods and applications /
Data science solutions with Python fast and scalable models using Keras, Pyspark Mllib, H2O, XGBoost, and scikit-Learn /
The cultural life of machine learning : an incursion into critical AI studies /
Data analysis, machine learning and knowledge discovery /
Beginning machine learning in the browser quick-start guide to gait analysis with JavaScript and TensorFlow.js /
Modern approaches in machine learning and cognitive science : a walkthrough : latest trends in AI /
Advanced machine learning technologies and applications Proceedings of AMLTA 2021 /
Machine learning in medicine-- Cookbook two /
Supervised learning with quantum computers /
The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019) /
Deep learning innovations and their convergence with big data /
Practicing Trustworthy Machine Learning.
Machine learning, blockchain technologies and big data analytics for IoTs : methods, technologies and applications /
Machine learning : theory and applications /
Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : concepts, tools, and techniques to build intelligent systems /
Probabilistic machine learning for civil engineers /
Hands-on intelligent agents with OpenAI Gym : a step-by-step guide to develop AI agents using deep reinforcement learning /
The deep learning video collection.
Scalable machine learning : complex data analysis at scale /
Up and running with deep learning /
Practical machine learning : tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques /
Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules.
Machine Learning Infrastructure and Best Practices for Software Engineers : Take Your Machine Learning Software from a Prototype to a Fully Fledged Software System /
Deep learning with TensorFlow : take your machine learning knowledge to the next level with the power of TensorFlow /
Building machine learning systems with a feature store /
Mastering .NET machine learning : master the art of machine learning with .NET and gain insight into real-world applications /
Getting started with TensorFlow /
Practical machine learning cookbook : resolving and offering solutions to your machine learning problems with R /
Machine learning under resource constraints.
Effective machine learning teams : best practices for ML practitioners /
Machine learning : hands-on for developers and technical professionals /
Machine learning with noisy labels : definitions, theory, techniques and solutions /
Klassifikation von Niederspannungsnetzen mit Support Vector Machines : Bewertung des Aufnahmevermögens für Dezentrale Erzeugungsanlagen /
Federated learning theory and practice /
Machine learning and big data concepts, algorithms, tools and applications /
Machine learning with Dynamics 365 and Power Platform the ultimate guide to apply predictive analytics /
Industrial applications of machine learning
Deep learning 		1031
Q325.5-.7 Digital Watermarking for Machine Learning Model Techniques, Protocols and Applications.
Guide to Deep Learning Basics Logical, Historical and Philosophical Perspectives /
Raspberry Pi Image Processing Programming : With NumPy, SciPy, Matplotlib, and OpenCV.
Practical Natural Language Processing with Python With Case Studies from Industries Using Text Data at Scale /
Multimodal Affective Computing Technologies and Applications in Learning Environments.
Building Computer Vision Applications Using Artificial Neural Networks With Step-by-Step Examples in OpenCV and TensorFlow with Python /
Machine Learning Paradigms Advances in Deep Learning-based Technological Applications /
Hands-on Time Series Analysis with Python From Basics to Bleeding Edge Techniques /
Supervised Learning with Python Concepts and Practical Implementation Using Python /
Machine Learning in the Oil and Gas Industry Including Geosciences, Reservoir Engineering, and Production Engineering with Python /
Deep Neural Evolution Deep Learning with Evolutionary Computation /
Artificial Neural Networks with TensorFlow 2 ANN Architecture Machine Learning Projects /
Practical Machine Learning with AWS Process, Build, Deploy, and Productionize Your Models Using AWS /
Hyperparameter Optimization in Machine Learning Make Your Machine Learning and Deep Learning Models More Efficient /
Beginning MLOps with MLFlow Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure /
Deploy Machine Learning Models to Production With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform /
Machine Learning and AI for Healthcare Big Data for Improved Health Outcomes /
Hands-on Question Answering Systems with BERT Applications in Neural Networks and Natural Language Processing /
TensorFlow 2.x in the Colaboratory Cloud An Introduction to Deep Learning on Google’s Cloud Service /
Data Science Revealed With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning /
Practical Machine Learning for Streaming Data with Python Design, Develop, and Validate Online Learning Models /
Transactional Machine Learning with Data Streams and AutoML Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python /
Advanced Forecasting with Python With State-of-the-Art-Models Including LSTMs, Facebook’s Prophet, and Amazon’s DeepAR /
Generating a New Reality From Autoencoders and Adversarial Networks to Deepfakes /
Machine Learning with PySpark With Natural Language Processing and Recommender Systems /
Deep Reinforcement Learning Fundamentals, Research and Applications /
Automation and Collaborative Robotics A Guide to the Future of Work /
Beginning Deep Learning with TensorFlow Work with Keras, MNIST Data Sets, and Advanced Neural Networks /
Oracle Digital Assistant A Guide to Enterprise-Grade Chatbots /
Practical Machine Learning with Rust Creating Intelligent Applications in Rust /
Robotic Process Automation using UiPath StudioX A Citizen Developer’s Guide to Hyperautomation /
Computer Vision Projects with PyTorch Design and Develop Production-Grade Models /
Machine Learning on Geographical Data Using Python Introduction into Geodata with Applications and Use Cases /
Hands-on AIOps Best Practices Guide to Implementing AIOps /
Raspberry Pi Image Processing Programming With NumPy, SciPy, Matplotlib, and OpenCV /
Designing Human-Centric AI Experiences Applied UX Design for Artificial Intelligence /
Applied Recommender Systems with Python Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques /
IoT Machine Learning Applications in Telecom, Energy, and Agriculture With Raspberry Pi and Arduino Using Python /
Hands-on Scikit-Learn for Machine Learning Applications Data Science Fundamentals with Python /
Machine Learning for Auditors Automating Fraud Investigations Through Artificial Intelligence /
Hands-on Machine Learning with Python Implement Neural Network Solutions with Scikit-learn and PyTorch /
Adaptive Machine Learning Algorithms with Python Solve Data Analytics and Machine Learning Problems on Edge Devices / 		45
Q325.5 .A232 2005 Human comprehensible machine learning : papers from the AAAI workshop / 1
Q325.5 .A26 2006eb Active conceptual modeling of learning next generation learning-base system development / 1
Q325.5 .A27 1995 Machine learning : neural networks, genetic algorithms, and fuzzy systems / 1
Q325.5 .A29 2010 Abstract state machines, Alloy, B and Z Second International Conference, ABZ 2010, Orford, QC, Canada, February 22-25, 2010 ; proceedings / 1
Q325.5 .A29 2012 Abstract state machines, Alloy, B, VDM, and Z third International Conference, ABZ 2012, Pisa, Italy, June 18-21, 2012. Proceedings / 1
Q325.5 .A29 2021 Rigorous state-based methods : 8th international conference, ABZ 2021, Ulm, Germany, June 9-11, 2021 : proceedings / 1
Q325.5 .A29 2023eb Rigorous state-based methods : 9th International Conference, ABZ 2023, Nancy, France, May 30-June 2, 2023, Proceedings / 1
Q325.5 .A295 2014 Advanced structured prediction / 1
Q325.5 .A295 2014eb Advanced structured prediction / 2
Q325.5 .A32 1999 Advances in kernel methods : support vector learning / 1
Q325.5 .A32 1999eb Advances in kernel methods : support vector learning / 1
Q325.5 .A34 2000 Advances in large margin classifiers / 1
Q325.5 .A34 2000eb Advances in large margin classifiers / 1
Q325.5 .A344 2001 Advances in learning classifier systems : third international workshop, IWLCS 2000, Paris, France, September 15-16, 2000 : revised papers / 1