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Deep Learning with Python

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Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.

In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

350 pages, Paperback

First published November 30, 2017

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About the author

François Chollet

21 books133 followers
François Chollet is a French engineer and researcher in artificial intelligence.

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Profile Image for Mèo lười.
193 reviews247 followers
September 7, 2020
Quyển này chính là Dế mèn phiêu lưu kí trong deep learning =,= nhẹ nhàng, dễ hiểu, dễ tưởng tượng.
Hiuhiu.
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