DeepAI
Log In Sign Up

An Introduction to Modern Statistical Learning

07/20/2022
by   Joseph G. Makin, et al.
0

This work in progress aims to provide a unified introduction to statistical learning, building up slowly from classical models like the GMM and HMM to modern neural networks like the VAE and diffusion models. There are today many internet resources that explain this or that new machine-learning algorithm in isolation, but they do not (and cannot, in so brief a space) connect these algorithms with each other or with the classical literature on statistical models, out of which the modern algorithms emerged. Also conspicuously lacking is a single notational system which, although unfazing to those already familiar with the material (like the authors of these posts), raises a significant barrier to the novice's entry. Likewise, I have aimed to assimilate the various models, wherever possible, to a single framework for inference and learning, showing how (and why) to change one model into another with minimal alteration (some of them novel, others from the literature). Some background is of course necessary. I have assumed the reader is familiar with basic multivariable calculus, probability and statistics, and linear algebra. The goal of this book is certainly not completeness, but rather to draw a more or less straight-line path from the basics to the extremely powerful new models of the last decade. The goal then is to complement, not replace, such comprehensive texts as Bishop's Pattern Recognition and Machine Learning, which is now 15 years old.

READ FULL TEXT

page 1

page 2

page 3

page 4

09/08/2017

A Brief Introduction to Machine Learning for Engineers

This monograph aims at providing an introduction to key concepts, algori...
08/20/2003

Artificial Neural Networks for Beginners

The scope of this teaching package is to make a brief induction to Artif...
04/26/2013

Introduction to Judea Pearl's Do-Calculus

This is a purely pedagogical paper with no new results. The goal of the ...
03/06/2020

AutoML-Zero: Evolving Machine Learning Algorithms From Scratch

Machine learning research has advanced in multiple aspects, including mo...
03/23/2018

A high-bias, low-variance introduction to Machine Learning for physicists

Machine Learning (ML) is one of the most exciting and dynamic areas of m...
02/08/2020

Majority Voting and the Condorcet's Jury Theorem

There is a striking relationship between a three hundred years old Polit...