This is a book from 2014 that is a decent starting point for diving into ML(Machine Learning.) There are exercises included in the book, and it seems to do a fairly good job of starting the reader from a point of almost no knowledge of ML to more complex subjects, many of which many people will never use. Don’t be fooled by the format. This is definitely a course textbook.
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering.
In all honesty, I’ve only browsed through parts of the book. It’s on my reading list, but like many people the sheer length of my reading list is far beyond any distance I’ll live long enough to travel.
The nice part about this book is that it’s free. If you do or don’t like it you don’t ever have to pay for it. There is a link to a full pdf copy of the book, free for individual use. There are also links to a Solution Manual in PDF, and some of the classes that have used the book.
If you like the book, please consider purchasing it at the link below.