Machine learning. The Science and Art of Building algorithms that Extract Knowledge from data
Here is one of the most interesting textbooks on machine learning - a section of artificial intelligence that studies methods for building models capable of learning and algorithms for their construction. The author paid tribute to the incredible richness of the subject and did not lose sight of the unifying principles. The reader is immersed in machine learning in action from the first pages, but without the technical details that are not necessary at first. As the subject is studied, carefully selected examples, accompanied by illustrations, gradually become more complicated. The book describes a wide range of logical, geometric and statistical models, and touches on such topics at the forefront of science as matrix factorization and RCP analysis. Special attention is paid to the most important role of signs. The established terminology is supplemented by the introduction of new useful concepts. At the end of each chapter there are links to additional literature with author's comments. The book is clearly written and well organized. Starting from the basics, the author skillfully guides the reader, introducing him to useful facts and describing in detail a number of machine learning methods. The pseudocode of key algorithms is also given. Thanks to all this, the book sets a new standard for studying such a complex discipline as machine learning.
No reviews found
