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. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. DESCRIPTIONDeep learning is applicable to a widening range of artificialintelligence problems, such as image classification, speech recognition,text classification, question answering, text-to-speech, and opticalcharacter recognition. Deep Learning with Python is structured around a series of practicalcode examples that illustrate each new concept introduced anddemonstrate best practices. By the time you reach the end of this book,you will have become a Keras expert and will be able to apply deeplearning in your own projects. KEY FEATURES • Practical code examples• In-depth introduction to Keras• Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGYDeep learning is the technology behind photo tagging systems atFacebook and Google, self-driving cars, speech recognition systems onyour smartphone, and much more. AUTHOR BIOFrancois Chollet is the author of Keras, one of the most widely usedlibraries for deep learning in Python. He has been working with deep neuralnetworks since 2012. Francois is currently doing deep learning research atGoogle. He blogs about deep learning at blog.keras.io.

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Pages: 384, Edition: 1st, Paperback, Manning Publications