introduction to keras throughout this bookthe code examples use keras (deep-learning framework for python that provides convenient way to define and train almost any kind of deep-learning model keras was initially developed for researcherswith the aim of enabling fast experimentation keras has the following key featuresit allows the same code to run seamlessly on cpu or gpu it has user-friendly api that makes it easy to quickly prototype deep-learning models it has built-in support for convolutional networks (for computer vision)recurrent networks (for sequence processing)and any combination of both it supports arbitrary network architecturesmulti-input or multi-output modelslayer sharingmodel sharingand so on this means keras is appropriate for building essentially any deep-learning modelfrom generative adversarial network to neural turing machine keras is distributed under the permissive mit licensewhich means it can be freely used in commercial projects it' compatible with any version of python from to (as of mid- keras has well over , usersranging from academic researchers and engineers at both startups and large companies to graduate students and hobbyists keras is used at googlenetflixubercernyelpsquareand hundreds of startups working on wide range of problems keras is also popular framework on kagglethe machine-learning competition websitewhere almost every recent deep-learning competition has been won using keras models figure google web search int erest for different deep-learning frameworks over ime licensed to