xvii who should read this book this book is written for people with python programming experience who want to get started with machine learning and deep learning but this book can also be valuable to many different types of readersif you're data scientist familiar with machine learningthis book will provide you with solidpractical introduction to deep learningthe fastest-growing and most significant subfield of machine learning if you're deep-learning expert looking to get started with the keras frameworkyou'll find this book to be the best keras crash course available if you're graduate student studying deep learning in formal settingyou'll find this book to be practical complement to your educationhelping you build intuition around the behavior of deep neural networks and familiarizing you with key best practices even technically minded people who don' code regularly will find this book useful as an introduction to both basic and advanced deep-learning concepts in order to use kerasyou'll need reasonable python proficiency additionallyfamiliarity with the numpy library will be helpfulalthough it isn' required you don' need previous experience with machine learning or deep learningthis book covers from scratch all the necessary basics you don' need an advanced mathematics backgroundeither--high school-level mathematics should suffice in order to follow along roadmap this book is structured in two parts if you have no prior experience with machine learningi strongly recommend that you complete part before approaching part we'll start with simple examplesand as the book goes onwe'll get increasingly close to state-of-the-art techniques part is high-level introduction to deep learningproviding context and definitionsand explaining all the notions required to get started with machine learning and neural networks presents essential context and background knowledge around aimachine learningand deep learning introduces fundamental concepts necessary in order to approach deep learningtensorstensor operationsgradient descentand backpropagation this also features the book' first example of working neural network includes everything you need to get started with neural networksan introduction to kerasour deep-learning framework of choicea guide for setting up your workstationand three foundational code examples with detailed explanations by the end of this you'll be able to train simple neural licensed to