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What it’s about

Deep Learning is the definitive textbook for students and professionals looking to master the field of artificial intelligence. Authored by three leading experts, this comprehensive guide starts with the essential mathematical foundations of linear algebra, probability, and optimization, builds up to the core modern deep learning practices like feedforward networks, convolutional nets, and recurrent nets, and finally explores the cutting edge of research in generative models and representation learning. Whether you're a student entering the field or a software engineer looking to apply these powerful techniques, this book provides the foundational knowledge, practical methodology, and forward-looking insights necessary to build and understand intelligent systems that learn from experience.

The through-line

Who it’s for

A university student or software engineer who wants to understand and apply deep learning to solve complex problems, but may lack a strong background in machine learning or statistics.

The problem

Solving complex, real-world tasks (like image recognition, speech processing, and machine translation) that are intuitive for humans but difficult to formalize with traditional programming or simple machine learning algorithms. Feeling overwhelmed by the complexity and rapid evolution of AI, uncertain about the mathematical foundations required, and frustrated by the challenge of building models that generalize beyond training data.

The plan

1. Master the foundational applied math and machine learning basics (Part I).
2. Learn the modern practices and established deep learning algorithms like CNNs and RNNs (Part II).
3. Explore the cutting edge of deep learning research and future directions (Part III).

The payoff

Gaining a deep, principled understanding of the theory and practice of deep learning. · Being able to confidently design, build, train, and debug state-of-the-art neural networks for various applications. · Becoming a competent researcher or practitioner capable of contributing to the field of AI.

See our guide

• Build AI Systems That Ship →
• AI Safety, Governance & Alignment Practice →

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