Machine Learning with Tensorflow
Overview
Summary Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology 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. About the Book 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. What's Inside
- 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. About the Author Author Nishant Shukla is a computer vision researcher focused on applying machine-learning techniques in robotics. Senior technical editor, Kenneth Fricklas, is a seasoned developer, author, and machine-learning practitioner. Table of Contents
- PART 1 - YOUR MACHINE-LEARNING RIG
- A machine-learning odyssey
- TensorFlow essentialsPART 2 - CORE LEARNING ALGORITHMS
- Linear regression and beyond
- A gentle introduction to classification
- Automatically clustering data
- Hidden Markov modelsPART 3 - THE NEURAL NETWORK PARADIGM
- A peek into autoencoders
- Reinforcement learning
- Convolutional neural networks
- Recurrent neural networks
- Sequence-to-sequence models for chatbots
- Utility landscape
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9781617293870
- ISBN-10: 1617293873
- Publisher: Manning Publications
- Publish Date: February 2018
- Dimensions: 9.2 x 7.4 x 0.5 inches
- Shipping Weight: 1 pounds
- Page Count: 272
Related Categories
