December 2018
Beginner to intermediate
684 pages
21h 9m
English
Content preview from Hands-On Machine Learning for Algorithmic Trading
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
Start your free trial
How to use Keras
Keras was designed as a high-level or meta API to accelerate the iterative workflow when designing and training deep neural networks with computational backends, such as TensorFlow, Theano, or CNTK. It has been integrated into TensorFlow in 2017 and is set to become the principal TensorFlow interface with the 2.0 release. You can also combine code from both libraries to leverage Keras' high-level abstractions as well as customized TensorFlow graph operations.
Keras supports both a slightly simpler sequential and more flexible Functional API. We will introduce the former at this point and use the Functional API in more complex examples in the following chapters.
To create a model, we just need to instantiate a sequential object ...