Description
Book SynopsisDESCRIPTION
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.
