The purpose of the 3rd edition of this book is to give a sound and self-contained (in the sense that the necessary probability theory is included) introduction to classical or mainstream statistical theory. It is not a statistical-methods-cookbook, nor a compendium of statistical theories, nor is it a mathematics book. The book is intended to be a ...
In a world where information has never been so accessible, and answers are available at the touch of a fingertip, we are hungrier for the facts than ever before - something the Covid-19 crisis has brought to light. And yet, paywalls put in place by multi-billion dollar publishing houses are still preventing millions from accessing quality, scientif...
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.
This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basi...
William Sharp (1855-1905) conducted one of the most audacious literary deceptions of his or any time. A Scottish poet, novelist, biographer, and editor, he began in 1893 to write critically and commercially successful books under the name Fiona Macleod who became far more than a pseudonym. Enlisting his sister to provide the Macleod handwriting, he...
The world of machine learning is evolving so quickly that it's challenging to find real-life use cases that are relevant to your day-to-day work.
That's why we've created this comprehensive guide you can start using right away. Get everything you need - use cases, code samples and notebooks - so you can start putting the Databrick...