Machine Learning with TensorFlow. Este artículo no está disponible.Machine Learning with TensorFlow

DESCRIPTION

Being able to make near-real-time decisions is becoming increasingly

crucial. To succeed, we need machine learning systems that can turn

massive amounts of data into valuable insights. But when you're just

starting out in the data science field, how do you get started creating

machine learning applications? The answer is TensorFlow, a new open

source machine learning library from Google. The TensorFlow library

can take your high level designs and turn them into the low level

mathematical operations required by machine learning algorithms.

Machine Learning with TensorFlow teaches readers about machine

learning algorithms and how to implement solutions with TensorFlow.

It starts with an overview of machine learning concepts and moves on

to the essentials needed to begin using TensorFlow. Each chapter

zooms into a prominent example of machine learning. Readers can

cover them all to master the basics or skip around to cater to their

needs. By the end of this book, readers will be able to solve

classification, clustering, regression, and prediction problems in the

real world.

KEY FEATURES

• Lots of diagrams, code examples, and exercises

• Solves real-world problems with TensorFlow

• Uses well-studied neural network architectures

• Presents code that can be used for the readers’ own applications

AUDIENCE

This book is for programmers who have some experience with Python and

linear algebra concepts like vectors and matrices. No experience with

machine learning is necessary.

ABOUT THE TECHNOLOGY

Google open-sourced their machine learning framework called TensorFlow

in late 2015 under the Apache 2.0 license. Before that, it was used

proprietarily by Google in its speech recognition, Search, Photos, and

Gmail, among other applications. TensorFlow is one the most popular

machine learning libraries.

AUTHOR BIO

Nishant Shukla is a computer vision researcher at UCLA, focusing on

machine learning techniques with robotics. He has been a developer for

Microsoft, Facebook, and Foursquare, and a machine learning engineer for

SpaceX, as well as the author of the Haskell Data Analysis Cookbook.