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Deep Learning

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Deep Learning

Av: John D. Kelleher
Berättare: Joel Richards
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Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.

Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.

©2019 Massachusetts Institute of Technology (P)2019 Gildan Media
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Very good ideas that are essential for everyone who wants to dive deeper into the deep learning field. It contains a bit too many details that are designed for a normal book not an audiobook such as formulas, which might be important for the mathematical nature of the subject but not as an audible material.

Great Book That Covers Essential Knowledge

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