The basics of deep learning. Creation of algorithms for the next generation artificial intelligence

Deep training is machine learning, which is built on the idea of ​​learning through examples. This book analyzes the basic ideas of this complex industry in the study of artificial intelligence. The authors set a goal to form a holistic idea of ​​how the tasks in the field of deep learning are solved, what concepts are used in this environment and how to introduce the corresponding algorithms.
With the revival of neural networks in the 2000s, deep training became an extremely actively developing field of research, which paves the path to modern machine learning. This book offers examples and interpretations that will help to understand the main ideas in this complex branch of knowledge. Large companies such as Google, Microsoft and Facebook drew attention to deep training and actively increase the staff of their units working in this area. For everyone else, it remains still a complex, complex and difficult to vibrant object. The studies are full of incomprehensible jargon, and scattered textbooks on the network do not give a proper idea of ​​how the tasks in this area are solved. The purpose of this book is to fill in this gap