In this chapter, an overview of the Keras environment has been explored. We have learned how to install and configure Keras and how to work with the keras library, and have discovered the basic concepts of the Keras architecture. We have also seen how Keras uses TensorFlow as its tensor manipulation library, how we can switch the Keras backend from TensorFlow, which is the default option, to Theano and CNTK, and other available frameworks. Finally, we have understood the different types of Keras model, and we discussed model classes used with sequential layers and those used with functional API layers.
In the next chapter, you will learn the different types of regression techniques and how to apply regression methods to your data, and will understand how the regression algorithm works. We will understand the basic concepts that multiple linear regression methods use to fit equations to data using Keras layers. We will also learn how to evaluate the model's performance, and learn how to tune a model to improve its performance.
