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.
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Paperback. Condition: As New. Softcover. Chinese text. Good binding and cover. Minor shelf wear. Clean, unmarked pages. Seller Inventory # 2301160003
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paperback. Condition: New. Paperback. Pub Date: 2018-08-01 Publisher: People's Posts and Telecommunications Press This book was written by Francois Chollet. the father of Keras and now a researcher at Google's artificial intelligence. with a detailed introduction to Python and Keras. Exploratory practice of deep learning. including computer vision. natural language processing. Seller Inventory # NK019859
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