The Programmer's AI Book: Start with Code

With the popularization of AI technology, how to quickly understand, master and apply AI technology has become an urgent problem for most programmers. This book is based on the Keras framework and focuses on code implementation. It provides detailed answers to common questions programmers have when learning AI algorithms, and establishes a clear logical system for the application of concepts such as machine learning and deep neural networks in actual projects. This book is divided into two parts. The first part (Chapter 1-4) can help readers understand and independently develop simpler machine learning applications, while the second part (Chapter 5-9) focuses on the three hot areas of AI technology: recommendation systems, natural language processing (NLP) and image processing. Among them, Chapter 1 quickly introduces the machine learning implementation of Keras through specific examples and gives the overall concept; Chapter 2 starts with simple neurons, guided by practical problems and code implementation, and gradually transitions to the specific implementation of multi-layer neural networks, explaining the working mode of neural networks from the code level; Chapter 3 explains the core concepts and usage methods of Keras, helping readers quickly get started with Keras; Chapter 4 explains machine learning Common concepts, definitions and algorithms in Xi; Chapter 5 introduces common solutions for recommendation systems, including different implementations of collaborative filtering and Wide&Deep models; Chapter 6 explains the principles of Recurrent Neural Networks (RNN) and the application of Seq2Seq, Attention and other technologies in natural language processing; Chapters 7 to 8 provide in-depth discussions on the classification and target recognition of image processing, and analyze Faster from the code level RCNN and YOLO v3 are two typical recognition algorithms; Chapter 9 introduces and introduces TensorFlow Serving for the engineering deployment of AI models.