Top 10 AI Books to Elevate Your Knowledge in 2025

Last Updated: January 29, 2025

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best selling books on AI — #best-selling books on artificial intelligence

Industries and life as we know it are being transformed by artificial intelligence, making it necessary to remain updated. Whether you are a novice or an expert, establishing a deeper understanding of AI is important to ensure greater opportunities and efficient navigation of various challenges.

The following set of books is aimed at providing pertinent information, intelligence, and practical skills that are critical to have. These resources are suitable for novices and fans of the craft and will help them understand the world of AI better and enable them to flourish in it.

1. “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig

Genre: Technical textbook
Summary: This is the definitive textbook on AI, covering topics from search algorithms to machine learning and robotics.
Why Recommended: Ideal for students and professionals looking for a comprehensive introduction to AI.
Target Audience: Beginners to intermediate learners.

Pros and Cons:
- Pros: Comprehensive, well-structured, widely used in universities.
- Cons: Dense for casual readers.
Publisher: Pearson
Publication year: 2009
Number of Pages: 1152 pages
Language: English

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2. “Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

Genre: Technical textbook
Summary: Covers deep learning concepts, including neural networks, optimization, and practical applications.
Why Recommended: Essential for understanding modern AI techniques and deep learning architectures.
Target Audience: Intermediate to advanced readers.
Pros and Cons:
- Pros: Authoritative, in-depth.
- Cons: Heavy on math and theory.
Publisher: The MIT Press
Publication year: 2016
Number of Pages: 800 pages
Language: English

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3. “Superintelligence: Paths, Dangers, Strategies” by Nick Bostrom

Genre: Non-technical/philosophical
Summary: Explores the implications of AI surpassing human intelligence.
Why Recommended: Offers critical insights into AI safety and ethics.
Target Audience: Anyone interested in the future of AI.
Pros and Cons:
- Pros: Thought-provoking, widely discussed.
- Cons: Philosophical, not technical.
Publisher: Oxford University Press
Publication year: 2016
Number of Pages: 432 pages
Language: English

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4. “Life 3.0: Being Human in the Age of Artificial Intelligence” by Max Tegmark

Genre: Non-technical
Summary: Discusses how AI might shape society and what it means for humanity.
Why Recommended: Accessible introduction to AI’s societal impact.
Target Audience: General readers.
Pros and Cons:
- Pros: Engaging, easy to read.
- Cons: Lacks technical depth.
Publisher: Knopf
Publication year: 2017
Number of Pages: 384 pages
Language: English

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5. “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” by Aurélien Géron

Genre: Practical/technical
Summary: A hands-on guide to machine learning and deep learning tools.
Why Recommended: Excellent for readers looking to get practical skills.
Target Audience: Beginners to intermediate practitioners.
Pros and Cons:
- Pros: Practical, code-focused.
- Cons: Requires programming knowledge.
Publisher: O’Reilly Media
Publication year: 2019
Number of Pages: 848 pages
Language: English

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6. “Prediction Machines: The Simple Economics of Artificial Intelligence” by Ajay Agrawal, Joshua Gans, and Avi Goldfarb

Genre: Non-technical/business
Summary: Explains how AI reduces the cost of prediction and its implications for business and decision-making.
Why Recommended: Great for understanding the economic impact of AI.
Target Audience: Business leaders, entrepreneurs, and general readers.
Pros and Cons:
- Pros: Accessible, practical insights for business.
- Cons: Less focus on technical aspects.
Publisher: Harvard Business Review Press
Publication year: 2018
Number of Pages: 272 pages
Language: English

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7. “You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place” by Janelle Shane

Genre: Non-technical/humorous
Summary: A humorous introduction to how AI works, filled with quirky examples.
Why Recommended: Makes AI concepts approachable and fun.
Target Audience: General readers and beginners.
Pros and Cons:
- Pros: Engaging, easy to follow, humorous.
- Cons: Light on technical depth.
Publisher: Voracious
Publication year: 2019
Number of Pages: 272 pages
Language: English

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8. “Machine Learning Yearning” by Andrew Ng

Genre: Practical/technical
Summary: A practical guide to structuring AI projects and solving common challenges.
Why Recommended: Written by a leading AI expert, it’s a valuable resource for practitioners.
Target Audience: Beginners and intermediate AI professionals.
Pros and Cons:
- Pros: Practical, clear, concise.
- Cons: Narrow focus on project management.
Publisher: Generic
Publication year: 2024
Number of Pages: 118 pages
Language: English

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9. “Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World” by Marco Iansiti and Karim R. Lakhani

Genre: Business/Strategy
Summary: Explores how AI transforms business models and competition.
Why Recommended: Insightful for leaders adapting to the AI-driven economy.
Target Audience: Executives, entrepreneurs, and strategists.
Pros and Cons:
- Pros: Strategic focus, practical case studies.
- Cons: Geared towards business readers.
Publisher: Harvard Business Review Press
Publication year: 2020
Number of Pages: 280 pages
Language: English

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10. “The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World” by Pedro Domingos

Genre: Non-technical/technical hybrid
Summary: Explains five major machine learning paradigms and their quest to create a “master algorithm.”
Why Recommended: A broad overview of AI and machine learning for general readers.
Target Audience: Beginners and enthusiasts.
Pros and Cons:
- Pros: Well-written, engaging.
- Cons: Less detail for advanced readers.
Publisher: Basic Books
Publication year: 2015
Number of Pages: 352 pages
Language: English