Deep Learning with Python

by François Chollet

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.

Genres: Programming, Artificial Intelligence, Computer Science, Technology, Nonfiction, Technical, Computers

350 pages, Paperback

First published November 30, 2017

About the author

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

Reviews

[J]

Fácil entendimento, com um material adequado em forma de notebooks.