We're living in a big data world. Being able to make near-real-time decisions becomes 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 that they use in their own successful products like Search, Maps, YouTube, Translate, and Photos. 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 you machine learning algorithms and how to implement solutions with TensorFlow. You'll start with an overview of machine learning concepts. Next, you'll learn the essentials you'll need to begin using TensorFlow before moving on to specific machine learning problems and solutions. With lots of diagrams, code examples, and exercises, this tutorial teaches you cutting-edge machine learning algorithms and techniques to solve them. Each chapter zooms into a prominent example of machine learning, such as classification, regression, anomaly detection, clustering, and neural networks. Cover them all to master the basics, or cater to your needs by skipping around. By the end of this book, you'll be able to solve classification, clustering, regression, and prediction problems in the real world.