• Title Deep Learning with Python
• Author(s) Francois Chollet
• Publisher: Manning Publications; 1 edition (December 22, 2017)
• Permission: Free to read entire book online by the publisher (Manning), 5 minutes every day.
• Hardcover/Paperback 384 pages
• eBook HTML
• Language: English
• ISBN-10/ASIN: 1617294438
• ISBN-13: 978-1617294433
• Share This:  

Book Description

This book introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.

• Deep learning from first principles
• Setting up your own deep-learning environment
• Image-classification models
• Deep learning for text and sequences
• Neural style transfer, text generation, and image generation

Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

• Francois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. He blogs about deep learning at blog.keras.io.

• Amazon

• Neural Networks and Deep Learning
• Python Programming
• Machine Learning
• Artificial Intelligence
• Data Analysis and Data Mining

• Deep Learning with Python (Francois Chollet)
• The Booke Homepage

• Python Machine Learning Projects (Brian Boucheron, et al)
• Deep Learning with JavaScript: Neural Networks in TensorFlow.js
• O'Reilly® Python Data Science Handbook: Essential Tools
• Deep Learning and the Game of Go (Max Pumperla, et al)