Free AI Books to Get You Started

Whether you’re looking to launch your career in Artificial Intelligence (AI) or simply want to learn more about this rapidly developing field, there are numerous resources available. These free books on AI, machine learning, and data science provide you with the fundamental knowledge needed to start your journey into the world of AI.

A must-read for those interested in AI, this book explains the underlying principles of how it works. The authors take an approach that is unique in the field and cover all aspects of AI, from the statistical foundation and algorithmic applications to ethical considerations and how businesses can leverage this technology.

This is the perfect resource for ML researchers and data scientists with limited software development skills. Written by an Amazon employee, this book dives into deep learning details without getting too overly complicated. It’s also updated on a regular basis, meaning you will be getting the latest and greatest in ML libraries.

The author of this book takes an interactive approach to ML, providing the reader with code examples, visuals, and real-life applications throughout each chapter. This book covers a wide range of ML methods from regression, decision trees, and SVM to neural networks and ensemble learning. It also discusses how to train and evaluate models, as well as deployment strategies and maintenance.

While this book was initially developed as a marketing feature for the software company Peltarion, it’s an excellent overview of how AI can be used to improve business operations and increase productivity. Using simple language, this resource is easy to understand and makes it clear how business leaders can make the most of AI to create positive change.

An extensive guide to AI programming, this book is ideal for readers who are familiar with the basics of computer science and have some experience with a programming language such as Python. It offers a unified introduction to the topic by teaching advanced Common Lisp techniques in the context of building major AI systems. It includes an extended AI programming project, the Automated Tourist Guide, that is integrated throughout the main chapters of the book.

Reinforcement learning is one of the hottest areas of AI research, and this book provides a concise and straightforward interpretation of its key ideas and algorithms. It also covers reinforcement learning in a way that is easily applied to real-world applications, such as fraud detection and online advertising.

The best thing about this book is that it’s written for non-computer science people, allowing them to get a solid understanding of the core concepts behind machine learning. It teaches you everything from the five core principles of AI to practical implementations with pseudocode, which can be used to test your own AI models. The book starts off with Python coding fundamentals in Chapter 3, before moving onto the real-world application of AI models, such as the Thompson Sampling model, in Chapter 5, and the Q-learning model in Chapter 9.Free AI books

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