1. /"Artificial intelligence: a modern approach/" by Stuart Russell and Peter Norvig
2. /"Neural networks and deep learning/" by Michael Nielsen
3. /"Machine learning: an algorithmic perspective/" by Stephen Marsland
4. /"The master algorithm/" by Pedro Domingos
5. //“Grokking Artificial Intelligence Algorithms/” by Joshua Eckroth
6. /"Artificial Intelligence for Humans/" by Jeff Heaton
7. /"Reinforcement learning: an introduction/" by Richard S. Sutton and Andrew G. Barto
8. /"Programming collective intelligence/" by Toby Segaran
9. /"Artificial Intelligence: Foundations of Computer Agents/" by David L. Poole and Alan K. Mackworth
10. /"Artificial Intelligence: A Guide to Intelligent Systems/" by Michael Negnevitsky

1. "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig: This classic textbook provides a comprehensive overview of AI, covering fundamental techniques and ideas for problem solving, knowledge representation, and machine learning. It is an essential resource for AI practitioners and researchers.

2. "Neural Networks and Deep Learning/" by Michael Nielsen: This book provides an in-depth introduction to neural networks and deep learning, exploring the basic concepts, algorithms, and applications of this powerful technology. This is an accessible guide to the fundamentals of neural networks.

3. /"Machine Learning: An Algorithmic Perspective/" by Stephen Marsland: This book provides a comprehensive overview of machine learning, focusing on fundamental algorithms and their implementation. It covers a wide range of topics, from supervised and unsupervised learning to deep learning and reinforcement learning.

4. /"The Master Algorithm/" by Pedro Domingos: This book explores the history and ideas of machine learning, providing an accessible introduction to the field and its potential applications. It provides a comprehensive overview of the field, from theory to practice.

5. /"Grokking Artificial Intelligence Algorithms/" by Joshua Eckroth: This book provides an accessible guide to the main AI algorithms, exploring how they work and how they can be used to solve real-world problems. It offers an in-depth look at the most important AI algorithms and how they can be implemented.

6. /"Artificial Intelligence for Humans/" by Jeff Heaton: This book provides an accessible introduction to the field of AI, offering a practical guide to creating AI applications. It covers the fundamentals of AI, from machine learning to natural language processing, and provides an overview of the most popular AI tools and libraries.

7. /"Reinforcement Learning: An Introduction/" by Richard S. Sutton and Andrew G. Barto: This classic textbook provides an in-depth introduction to reinforcement learning, exploring both the fundamentals of the field and its applications. This is an essential resource for those interested in developing and applying reinforcement learning algorithms.

8. /"Programming Collective Intelligence/" by Toby Segaran: This book provides an introduction to the fundamentals of data science and machine learning, exploring the most popular algorithms and how they can be applied to solve problems. real world problems. This is a comprehensive guide to the tools and techniques of modern data science.

9. /"Artificial Intelligence: Foundations of Computational Agents/" by David L. Poole and Alan K. Mackworth: This textbook provides an introduction to the field of AI, focusing on the foundations of intelligent agents and the algorithms that enable them. pilot. It covers a wide range of topics, from search algorithms to planning and learning algorithms.

10. /"Artificial Intelligence: A Guide to Intelligent Systems/" by Michael Negnevitsky: This book provides an introduction to AI, exploring the fundamentals of the field and its applications in real-world scenarios. This is a comprehensive guide to the principles of AI and its potential real-world applications.

1. The Definitive Guide to AI Books
2. 10 Essential AI Books You Should Read Now
3. Unleash the Power of AI: The 10 Best Books to Get Started
4. Get started with AI: 10 must-read books
8. Mastering the Basics of AI: 10 Essential Books
9. Take Your AI Knowledge to the Next Level: 10 Must-Read Books
10. From Beginner to Expert: 10 AI Books to Read

AI, Artificial Intelligence, Books, Reading, Learning, Machine Learning, Algorithms, Programming, Data Science, Neural Networks, Deep Learning, Reinforcement Learning, Jeff Heaton, Stuart Russell, Peter Norvig, Michael Nielsen, Stephen Marsland, Pedro Domingos , Joshua Eckroth, Richard S. Sutton, Andrew G. Barto, Toby Segaran, David L. Poole, Alan K. Mackworth, Michael Negnevitsky, Guide, Intelligent Systems, Computer Agents, Algorithmic Perspective, Modern Approach, Fundamentals of Computer Agents, Algorithms artificial intelligence Grokking, Master Algorithm, Artificial Intelligence for Humans, Collective Intelligence Programming

Please take the opportunity to connect and share this video with your friends and family if you find it useful.