![Machine Learning with R](/uploads/posts/2017-11/1511722580_cov350m.jpg)
Автор: Abhijit Ghatak
Издательство: Springer
ISBN: 9811068070
Год: 2017
Страниц: 224
Язык: английский
Формат: epub, azw3, pdf
Размер: 10.86 MB
This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it’s applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning. In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications.