Books / AI and ML

AI and ML

All Programming languages 1299AI and ML 661Algorithms and theory 472Software Development 391WEB development 334DevOps and Infrastructure 233Cybersecurity 218Databases 144OS and System 143Game development 122Embedded systems 122Other 109IT management 100
All Data Science 209Machine learning 133Neural networks 87LLM 85ChatGPT 31TensorFlow 27Computer Vision 24PyTorch 19MLOps 17Natural Language Processing 12熊猫 9AI Agents 1
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Python Tools for Data Scientists Pocket Primer

Python Tools for Data Scientists Pocket Primer

A

Oswald Campesato

AI and ML
EN
Deep Learning for Crack-Like Object Detection

Deep Learning for Crack-Like Object Detection

A

Kaige Zhang, Heng-Da Cheng

AI and ML
EN
Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

A

Ben Auffarth

AI and ML
EN
Understanding Large Language Models: Learning Their Underlying Concepts and Technologies

Understanding Large Language Models: Learning Their Underlying Concepts and Technologies

A

Thimira Amaratunga

AI and ML
EN
Pro Deep Learning with TensorFlow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

Pro Deep Learning with TensorFlow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

A

Santanu Pattanayak

AI and ML
EN
MLOps Lifecycle Toolkit: A Software Engineering Roadmap for Designing, Deploying, and Scaling Stochastic Systems

MLOps Lifecycle Toolkit: A Software Engineering Roadmap for Designing, Deploying, and Scaling Stochastic Systems

A

Dayne Sorvisto

AI and ML
EN
Beginner’s Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

Beginner’s Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

B

Sujay Raghavendra

AI and ML
EN
Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python, Second Edition

Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python, Second Edition

A

Shamshad Ansari

AI and ML
EN
Analytics Engineering with SQL and dbt: Building Meaningful Data Models at Scale

Analytics Engineering with SQL and dbt: Building Meaningful Data Models at Scale

A

Rui Machado, Hélder Russa

AI and ML
EN
Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

A

Kumar Abhishek, Dr. Mounir Abdelaziz

AI and ML
EN
Pandas for Everyone: Python Data Analysis. Second Edition

Pandas for Everyone: Python Data Analysis. Second Edition

A

Daniel Y. Chen

AI and ML
EN
Streaming Data Mesh: A Model for Optimizing Real-Time Data Services

Streaming Data Mesh: A Model for Optimizing Real-Time Data Services

A

Hubert Dulay, Stephen Mooney

AI and ML
EN
Hands-on Guide to Apache Spark 3: Build Scalable Computing Engines for Batch and Stream Data Processing

Hands-on Guide to Apache Spark 3: Build Scalable Computing Engines for Batch and Stream Data Processing

A

Alfonso Antolínez García

AI and ML
EN
Learning Pandas 2.0: A Comprehensive Guide to Data Manipulation and Analysis for Data Scientists and Machine Learning Professionals

Learning Pandas 2.0: A Comprehensive Guide to Data Manipulation and Analysis for Data Scientists and Machine Learning Professionals

A

Matthew Rosch

AI and ML
EN
Web Data Mining with Python: Discover and extract information from the web using Python

Web Data Mining with Python: Discover and extract information from the web using Python

A

Dr. Ranjana Rajnish, Dr. Meenakshi Srivastava

AI and ML
EN
Practical Machine Learning on Databricks

Practical Machine Learning on Databricks

A

Debu Sinha

AI and ML
RU
Pandas in Action

Pandas in Action

A

Борис Пасхавер

AI and ML
RU
Data Science in Action. Five Real Python Projects

Data Science in Action. Five Real Python Projects

A

Леонард Апельцин

AI and ML
EN
Training Data for Machine Learning: Human Supervision from Annotation to Data Science

Training Data for Machine Learning: Human Supervision from Annotation to Data Science

A

Anthony Sarkis

AI and ML
EN
Coding All-in-One For Dummies, 2nd Edition

Coding All-in-One For Dummies, 2nd Edition

A

Chris Minnick, Nikhil Abraham, Barry Burd, Eva Holland, Luca Massaron, John Paul Mueller

AI and ML
RU
Deep Learning with Python. Second Edition

Deep Learning with Python. Second Edition

B

Франсуа Шолле

AI and ML
RU
PyTorch. Illuminating Deep Learning

PyTorch. Illuminating Deep Learning

A

Эли Стивенс, Лука Антига, Томас Виман

AI and ML
EN
The Book of Dash: Build Dashboards with Python and Plotly

The Book of Dash: Build Dashboards with Python and Plotly

A

Adam Schroeder, Christian Mayer, Ann Marie Ward

AI and ML
EN
Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

A

Barr Moses, Lior Gavish, Molly Vorwerck

AI and ML
EN
Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

A

Aurélien Géron

AI and ML
EN
Data Visualization with Python and JavaScript: Scrape, Clean, Explore, and Transform Your Data

Data Visualization with Python and JavaScript: Scrape, Clean, Explore, and Transform Your Data

A

Kyran Dale

AI and ML
EN
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

A

Steven L. Brunton, J. Nathan Kutz

AI and ML
RU
Practical Data Analytics. Data Collection, Processing, and Visualization with Python

Practical Data Analytics. Data Collection, Processing, and Visualization with Python

A

Игорь Семичев

AI and ML
RU
Interactive dashboards and applications with Plotly and Dash. Harness the full power of a comprehensive web framework in Python – no JavaScript required.

Interactive dashboards and applications with Plotly and Dash. Harness the full power of a comprehensive web framework in Python – no JavaScript required.

A

Элиас Даббас

AI and ML
RU
Deep Learning Patterns and Practices

Deep Learning Patterns and Practices

A

Эндрю Ферлитш

AI and ML
RU
Theoretical Minimum in Computer Science. Networks, Cryptography, and Data Science

Theoretical Minimum in Computer Science. Networks, Cryptography, and Data Science

A

Владстон Феррейра Фило, Мото Пиктет

AI and ML
RU
Explainable AI Models in Python. AI Model. Explanations Using Python-Based Libraries, Extensions, and Frameworks.

Explainable AI Models in Python. AI Model. Explanations Using Python-Based Libraries, Extensions, and Frameworks.

A

Прадипта Мишра

AI and ML
RU
Computer Vision. Modern Methods and Development Prospects

Computer Vision. Modern Methods and Development Prospects

A

Рой Дэвис, Мэтью Терк (ред.)

AI and ML
RU
Applying OpenCV Functions in Computer Vision (60 Python Examples)

Applying OpenCV Functions in Computer Vision (60 Python Examples)

A

С.А. Молодяков

AI and ML
RU
Human-in-the-loop machine learning

Human-in-the-loop machine learning

A

Роберт (Манро) Монарх

AI and ML
RU
Machine Learning: Fundamentals, Algorithms, and Practical Applications

Machine Learning: Fundamentals, Algorithms, and Practical Applications

A

Джереми Уатт, Реза Борхани, Аггелос К. Катсаггелос

AI and ML
RU
Machine Learning. Design Patterns

Machine Learning. Design Patterns

A

Валлиаппа Лакшманан, Сара Робинсон, Майкл Мунн

AI and ML
RU
Mastering Transformer Architecture. Developing Modern Models with Advanced Natural Language Processing Techniques

Mastering Transformer Architecture. Developing Modern Models with Advanced Natural Language Processing Techniques

A

Саваш Йылдырым, Мейсам Асгари-Ченаглу

AI and ML
RU
Deep Learning with fastai and PyTorch: Minimal Formulas, Minimal Code, Maximum Efficiency

Deep Learning with fastai and PyTorch: Minimal Formulas, Minimal Code, Maximum Efficiency

A

Джереми Ховард и Сильвейн Гуггер

AI and ML
RU
Deep Reinforcement Learning: Theory and Practice in Python

Deep Reinforcement Learning: Theory and Practice in Python

A

Лаура Грессер, Ван Лун Кенг

AI and ML
RU
Deep Learning. The Shortest and Clearest Course

Deep Learning. The Shortest and Clearest Course

A

Джон Д. Келлехер

AI and ML
RU
Big Data. Why, What, and How?

Big Data. Why, What, and How?

A

Алена Запорожан

AI and ML
RU
Biological and Computer Vision

Biological and Computer Vision

A

Гэбриел Крейман

AI and ML
RU
Terrence Sejnowski. The Machine Learning Anthology. The Most Important AI Research of the Last 60 Years

Terrence Sejnowski. The Machine Learning Anthology. The Most Important AI Research of the Last 60 Years

A

Терренс Сейновски

AI and ML
RU
Analyzing Data in Microsoft Power BI. Preparing for the DA-100 Exam

Analyzing Data in Microsoft Power BI. Preparing for the DA-100 Exam

A

Даниил Маслюк

AI and ML
RU
Data Science Algorithms and Their Practical Implementation in Python

Data Science Algorithms and Their Practical Implementation in Python

B

А. В. Протодьяконов, П. А. Пылов, В. Е. Садовников

AI and ML
EN
Machine Learning Simplified: A Gentle Introduction to Supervised Learning

Machine Learning Simplified: A Gentle Introduction to Supervised Learning

A

Andrew Wolf

AI and ML
EN
Machine Learning and Data Science: Fundamentals and Applications

Machine Learning and Data Science: Fundamentals and Applications

A

Prateek Agrawal, Charu Gupta, Anand Sharma, Vishu Madaan, Nisheeth Joshi

AI and ML
EN
Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics

Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics

A

Thomas Nield

AI and ML
EN
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

A

Chip Huyen

AI and ML
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