if you've picked up this bookyou're probably aware of the extraordinary progress that deep learning has represented for the field of artificial intelligence in the recent past in mere five yearswe've gone from near-unusable image recognition and speech transcriptionto superhuman performance on these tasks the consequences of this sudden progress extend to almost every industry but in order to begin deploying deep-learning technology to every problem that it could solvewe need to make it accessible to as many people as possibleincluding nonexperts--people who aren' researchers or graduate students for deep learning to reach its full potentialwe need to radically democratize it when released the first version of the keras deep-learning framework in march the democratization of ai wasn' what had in mind had been doing research in machine learning for several yearsand had built keras to help me with my own experiments but throughout and tens of thousands of new people entered the field of deep learningmany of them picked up keras because it was--and still is--the easiest framework to get started with as watched scores of newcomers use keras in unexpectedpowerful waysi came to care deeply about the accessibility and democratization of ai realized that the further we spread these technologiesthe more useful and valuable they become accessibility quickly became an explicit goal in the development of kerasand over few short yearsthe keras developer community has made fantastic achievements on this front we've put deep learning into the hands of tens of thousands of peoplewho in turn are using it to solve important problems we didn' even know existed until recently the book you're holding is another step on the way to making deep learning available to as many people as possible keras had always needed companion course to xiii licensed to