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This book is an exploration of Keras, a deep learning library developed in Python. The author begins by helping you understand more details about the keras library to help you understand where and how you can use it. The various Keras layers have been discussed; hence you will know what you can use them for. Keras comes with various optimizers that you can use to optimize your deep learning models. These have been discussed in detail. The cost functions provided by the library have also been explored in detail. The various metrics used to measure the performance of models developed in Keras have been discussed. Keras can be used for performing basic classification tasks. You will learn this in details. It is also a good library for image classification tasks. The author has explored this. Text classification is a common task today in data processing. The author helps you know how to perform this task with the Keras library. Advanced Keras features such as checkpoints and callbacks have also been discussed.

The table of content is:

- What is Keras model?

- Basic Classification Tasks with Keras

- Keras for Image Classification

- Keras for Text Classification

- Advanced Keras

Tags: python, keras python, scikit learn, deeplearning4j, tensorflow keras, keras deep learning, numpy python, python programming, theano, keras tensorflow, deep learning with keras, cntk, python tensorflow, lambda.