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Continue your dive into deep learning. Explore learning resources on AI, accelerated computing, and accelerated data science.

Learning Deep Learning

Get started with deep learning with this new book from NVIDIA’s Magnus Ekman.

Learning Deep Learning is a complete guide to deep learning. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others—-including those with no prior machine learning or statistics experience. The book provides concise, well-annotated code examples using TensorFlow with Keras. And with corresponding PyTorch examples provided online, the book covers the two dominating Python libraries used for deep learning in industry and academia.

Book: Learning Deep Learning

Recommended Reading List

Book: Deep Learning (Adaptive Computation and Machine Learning)

Deep Learning (Adaptive Computation and Machine Learning)

by Ian Goodfellow, Yoshua Bengio, & Aaron Courville

Book: Deep Learning with Python

Deep Learning with Python

by François Chollet

Book: Ray Tracing Gems II

Ray Tracing Gems II

by Adam Marrs, Peter Shirley, & Ingo Wald

Book: Parallel Programming: Concepts and Practice

Parallel Programming: Concepts and Practice

by Bertil Schmidt Jorge Gonzalez-Dominguez, Christian Hundt, & Moritz Schlarb

Book: Professional CUDA C Programming

Professional CUDA C Programming

by John Cheng, Max Grossman & Ty McKercher

NVIDIA Research

Groundbreaking technology begins right here with the world’s leading researchers. Explore various research activities in AI,  deep learning, robotics, high-performance computing, computer graphics, and more.

Deep Learning programs for instructors

Educator Programs and
Teaching Kits

NVIDIA DLI offers downloadable course materials for university educators and free self-paced, online training to students through DLI Teaching Kits. Educators can also get certified to teach DLI workshops on campus through the University Ambassador Program.