Grokking Deep Learning

Grokking Deep Learning

作者: Andrew Trask
出版社: Manning
出版在: 2019-01-29
ISBN-13: 9781617293702
ISBN-10: 1617293709
裝訂格式: Paperback
總頁數: 325 頁





內容描述


An excellent introduction and overview of deep learning by a masterful teacher who guides, illuminates, and encourages you along the way.
-  Kelvin D. Meeks, International Technology Ventures

 
Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks.
about the technology
Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning.
about the book
Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you’ll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you’re done, you’ll be fully prepared to move on to mastering deep learning frameworks.
what's inside

The science behind deep learning
Building and training your own neural networks
Privacy concepts, including federated learning
Tips for continuing your pursuit of deep learning

about the reader
For readers with high school-level math and intermediate programming skills.
about the author
Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world’s largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform.




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