Machine Learning and Artificial Intelligence Books (Free Download in PDF)

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by Navdeep Singh Gill

Harness the power of generative AI to automate complex workflows and accelerate digital transformation in business environments.

Print length: 330 pages

Published: September 26, 2023

ISBN: 978-9355518590 (ISBN10: 9355518595)

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Machine Learning System Design

by Valerii Babushkin, Arseny Kravchenko

Learn how to architect reliable and scalable machine learning systems for real-world applications using industry best practices.

Print length: 376 pages

Published: February 25, 2025

ISBN: 978-1633438750 (ISBN10: 1633438759)

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Starting Data Analytics with Generative AI and Python

by Artur Guja, Marlena Siwiak, Marian Siwiak

It introduces foundational analytics techniques using Python, enhanced with the power of generative AI models.

Print length: 360 pages

Published: November 19, 2024

ISBN: 978-1633437210 (ISBN10: 1633437213)

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Hands-On Machine Learning with C++

by Kirill Koladiazhnyi

The guide offers practical examples for implementing machine learning algorithms with C++ for high-performance applications.

Print length: 530 pages

Published: May 15, 2020

ISBN: 978-1789955330 (ISBN10: 1789955335)

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Innovations in Optimization and Machine Learning

by Toufik Mzili

The book presents the latest research and practical techniques combining optimization theory and ML applications.

Print length: 504 pages

Published: September 13, 2024

ISBN: 979-8369352311 (ISBN10: 836935231A)

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Machine Learning Interviews

by Susan Shu Chang

It is a practical guide for aspiring ML engineers, featuring interview questions, coding challenges, and expert advice for succeeding in technical interviews.

Print length: 307 pages

Published: January 9, 2024

ISBN: 978-1098146542 (ISBN10: 1098146549)

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Prompt Engineering for LLMs

by John Berryman, Albert Ziegler

It provides in-depth guidance on optimizing prompts for large language models, enhancing the accuracy and relevance of AI-generated content.

Print length: 280 pages

Published: December 10, 2024

ISBN: 978-1098156152 (ISBN10: 1098156153)

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Generative AI for Cloud Solutions

by Paul Singh, Anurag Karuparti

This book provides a comprehensive guide to integrating AI into cloud systems, enabling smarter, more efficient operations.

Print length: 300 pages

Published: April 22, 2024

ISBN: 978-1835084786 (ISBN10: 1835084788)

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Distributed Machine Learning Patterns

by Yuan Tang

It offers practical techniques for scaling and deploying machine learning models in distributed environments to maximize efficiency and performance.

Print length: 248 pages

Published: January 2, 2024

ISBN: 978-1617299025 (ISBN10: 1617299022)

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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

by Aurélien Géron

It provides practical tools, concepts, and techniques for building intelligent systems using leading ML frameworks.

Print length: 861 pages

Published: November 8, 2022

ISBN: 978-1098125974 (ISBN10: 1098125975)

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With each year, artificial intelligence (AI) firmly establishes its position in various spheres of life. This triggers increased interest in learning in this area, making it important to have access to quality sources of knowledge. The market offers a multitude of books on AI, but for effective learning, it's crucial to choose the best among them.

Best Artificial Intelligence Books

Selecting the right educational materials is considered key to a deep understanding of AI. Not all textbooks are equally useful, and many of them offer only a superficial acquaintance with the topic.

The best artificial intelligence books for beginners not only introduce the basics of technology but also guide through complex concepts, emphasizing the practical application of knowledge.

AI Books for Beginners in PDF

When choosing artificial intelligence books for beginners in PDF, consider your current level of knowledge and interests. Here are a few tips for selection:

Beginners should look for guides that offer a basic introduction to artificial intelligence, explaining fundamental principles and terminology.
Those who already have basic knowledge might prefer literature that deepens understanding of machine learning and neural networks.
Professionals might be interested in materials focusing on specific algorithms, training methodologies, and their practical application in development.
Theoretical enthusiasts should seek books covering the philosophical and ethical aspects of AI.

Self-education in the field of artificial intelligence and machine learning is considered an important step towards mastering one of the most promising areas of the modern age. Choosing quality educational materials will not only allow for a deeper understanding of AI but also teach how to apply the acquired knowledge in practice.

Thanks to the availability of artificial intelligence books in PDF, knowledge of the latest achievements and methods in AI and machine learning has become even more accessible to a wide range of readers.