Chris Albon

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modelin...

Learn how to write modern, effective Python 3 code with Fluent Python. Author Luciano Ramalho guides you through the language's core features and libraries, teaching you how to make your code faster, shorter, and more readable. Discover and apply idiomatic Python 3 features and avoid wasting time trying to fit in patterns from other languages. This updated edition of the hands-on guide includes major updates on control flow, data structures, object-oriented idioms, and metaprogramming.

Learn the necessary math skills for political science and sociology with A Mathematics Course for Political and Social Research. This unique textbook is designed specifically for social science students and researchers, covering fundamental building blocks of math, basic algebra, calculus, linear algebra, and probability, among other essential subjects. With practical examples, numerous exercises, and a complete online solutions manual, it's an ideal reference for beginners and experts alike. Don't miss out on the opportunity to build (or refresh) your math skills in the social sciences with this invaluable resource.

Follow Kvothe's journey from a young boy in a traveling troupe to one of the most renowned magicians in his world. This captivating first-person narrative takes readers through the highs and lows of Kvothe's life, including his time as a near-feral orphan and his daring entrance into a legendary school of magic. Immerse yourself in the mind and body of a wizard in this thrilling novel.

This book explores the fascinating world of deep learning, which teaches computers to understand the world through a hierarchy of concepts. It covers mathematical and conceptual background, techniques used in industry, and research perspectives. Readers will learn about relevant topics in linear algebra, probability theory, and more, as well as practical applications in areas like natural language processing and computer vision. Perfect for students or engineers looking to incorporate deep learning into their work. Supplementary material available on the website.