Probability and Statistics for Machine Learning: A Textbook
English | 2024 | ISBN: 3031532813 | 538 Pages | PDF  (True) | 43 MB

From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.

https://rapidgator.net/file/b897db11039e415223cb96988f3128d2/

https://nitroflare.com/view/CC2806E2BC0D88B/

https://turbobit.net/0r8du58om9av.html