Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the al[...]
Along with updating all chapters and Python code examples, the second edition of this bestseller includes new chapters on Gaussian processes, Boltzmann machines, and deep belief networks. It also revises coverage of kernel methods and adds new material on random forests and model selection. The book[...]