As artificial intelligence continues to grow in complexity and influence, access to trustworthy and comprehensive educational resources has never been more important. In 2025, ten standout books on artificial intelligence are available for free, offering deep insights into machine learning, neural networks, ethical AI, and real-world applications. Whether you’re a student, researcher, or professional, these books provide a well-rounded foundation in the field of AI.

1. Demystifying Artificial Intelligence
   Authored by Emmanuel Gillain, this book simplifies the core ideas of AI. It explains distinctions between AI and machine learning, compares symbolic and statistical AI, and outlines how machines learn and solve problems. The book emphasizes ethical concerns, transparency, and responsible AI development.
2. Unlocking Artificial Intelligence
   Written by Christopher Mutschler, Christian Münzenmayer, Norman Uhlmann, and Alexander Martin, this book dives deep into theoretical models and real-world applications. It explores reinforcement learning, data-driven approaches, and AI applications in industry, bridging the gap between academic theory and business use cases.
3. Artificial Intelligence and Evaluation
   Steffen Bohni Nielsen, Francesco Mazzeo Rinaldi, and Gustav Jakob Petersson focus on the intersection of AI and evaluation methodologies. They discuss how AI is reshaping monitoring and assessment frameworks, highlight associated risks, and provide practical case studies to showcase both benefits and concerns.
4. Artificial Intelligence: Foundations of Computational Agents (3rd Edition)
   David L. Poole and Alan K. Mackworth present a structured exploration of AI agents. The book covers planning, reasoning under uncertainty, learning systems, and decision-making processes. It serves as an academic yet accessible introduction to computational intelligence.
5. Neural Networks
   This collaborative work by Ranjodh Singh Dhaliwal, Théo Lepage-Richer, and Lucy Suchman delves into the historical, cultural, and scientific significance of neural networks. The authors explore the societal contexts and philosophical implications of neural models across various disciplines.
6. AI Blueprints
   This book provides hands-on guidance to build AI solutions using practical examples. It’s ideal for readers with some programming experience looking to move beyond theory and develop tangible projects.
7. An Introduction to Machine Learning
   Aimed at beginners, this book introduces core machine learning concepts, including supervised and unsupervised learning, classification algorithms, and model evaluation. It also emphasizes mathematical underpinnings in a reader-friendly format.
8. Deep Learning and the Game of Go
   This innovative book uses the game of Go to illustrate deep learning principles. Readers learn about neural networks, policy and value networks, and reinforcement learning through the lens of strategic gameplay.
9. Ethics of Artificial Intelligence
   Focusing on moral and philosophical concerns, this book explores the ethical challenges posed by AI. Topics include algorithmic bias, surveillance, and the impact of automation on human labor and society.
10. You Look Like a Thing and I Love You
    Janelle Shane’s entertaining yet informative book offers real-world examples of how AI systems behave in unpredictable ways. Using humor and clear explanations, it demystifies the limitations and quirks of machine intelligence.

These ten books, available for free, offer a comprehensive and diverse entry point into the field of artificial intelligence. From technical deep-dives to ethical discussions, this collection reflects the evolving landscape of AI in 2025 and equips readers to engage with it critically and creatively.