Grokking Deep Learning
Andrew Trask
- 出版商: Manning
- 出版日期: 2019-01-25
- 售價: $1,650
- 貴賓價: 9.5 折 $1,568
- 語言: 英文
- 頁數: 325
- 裝訂: Paperback
- ISBN: 1617293709
- ISBN-13: 9781617293702
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相關分類:
DeepLearning 深度學習
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相關翻譯:
深度學習圖解 (Grokking Deep Learning) (簡中版)
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商品描述
An excellent introduction and overview of deep learning by a masterful teacher who guides, illuminates, and encourages you along the way.
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.