Basic Mathematics for Artificial Intelligence. Next-Level Mathematics for Effective and Successful AI Systems

The book provides a solid foundation in the mathematics underlying modern AI systems. It presents the necessary and sufficient information for successful work in the field of AI, without delving into complex academic theories, focusing on practical application and modern models. It covers the fundamentals of machine learning and data science. Topics include regression, neural networks, convolution, optimization, probability, Markov processes, differential equations, and much more, all exclusively in the context of artificial intelligence. It shows how to combine machine learning models and natural language, work with graph and network data, visualize space transformations, reduce dimensionality, process images, and select models for data-driven projects.