This book is divided into two parts, with a total of 12 chapters. Chapters 1 to 5 introduce the ontology of big data, basic theories of machine learning, etc., Laying the foundation for the practice of specific scenarios and algorithms. Readers can understand how similar the process of processing and transforming big data in engineering practice is to the process of humans learning knowledge and transforming it into practice. In the introduction to machine learning, a basic explanation of its mathematical principles and training process will be given, supplemented by code to help readers understand the use of technical tools in real scenarios. Chapters 6 to 12 provide multiple different use cases, and the chapters are independent of each other, introducing how to use artificial intelligence technology (natural language processing, fuzzy systems, genetic programming, swarm intelligence, reinforcement learning, network security, cognitive computing) to implement big data automation solutions.
If the reader has a certain understanding of the Java programming language, distributed computing framework, and various machine learning algorithms, then this book can help you establish an overall view and look at the application of artificial intelligence technology in big data from a broader perspective. If the reader knows nothing about the above knowledge, but is very interested in the technology and business of big data artificial intelligence, then he can get a cognitive improvement from zero to one through this book.
Reader comments
This book is quite good and has rich content. It not only introduces the basic theory of big data and machine learning, but also shows how to apply these technologies through specific use cases. I especially liked the practical part of the book, which helped me better understand the use of technical tools through code examples. This is a book worth reading for anyone interested in artificial intelligence and big data.
This book is quite good and has rich content. It not only introduces the basic theory of big data and machine learning, but also shows how to apply these technologies through specific use cases. I especially liked the practical part of the book, which helped me better understand the use of technical tools through code examples. This is a book worth reading for anyone interested in artificial intelligence and big data.