Machine Learning with TensorFlow
MEAP Edition, Version 10
By 作者: Nishant Shukla
ISBN-10 书号: 1617293873
ISBN-13 书号: 9781617293870
Edition 版本: 1
Release Finelybook 出版日期: 2018-02-12
pages 页数: 272
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python.
TensorFlow, Google’s library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You’ll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you’ll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own.
Matching your tasks to the right machine-learning and deep-learning approaches
Visualizing algorithms with TensorBoard
Understanding and using neural networks
About the Reader
Written for developers experienced with Python and algebraic concepts like vectors and matrices.
Part 1.Your machine-learning rig
Chapter 1.A machine-learning odyssey
Chapter 2.TensorFlow essentials
Part 2.Core learning algorithms
Chapter 3.Linear regression and beyond
Chapter 4.A gentle introduction to classification
Chapter 5.Automatically clustering data
Chapter 6.Hidden Markov models
Part 3.The neural network paradigm
Chapter 7.A peek into autoencoders
Chapter 8.Reinforcement learning
Chapter 9.Convolutional neural networks
Chapter 10.Recurrent neural networks
Chapter 11.Sequence-to-sequence models for chatbots
Chapter 12.Utility landscape