Pattern Recognition and Machine Learning

Machine Learning Pattern Recognition

Introduction These lecture notes were written to provide you with a handy reference to the material that was presented in the Machine Learning: Pattern Recognition course. It is not meant to replace the book of the course [Bishop, 2007], rather, it is meant to illustrate topics that may seem a bit dry or emphasise subjects that are deemed important to this class. It will often repeat what was s...

Machine Learning and Pattern Recognition

Pattern Recognition and Machine Learning

his book provides an introduction to the eld of pattern recognition and machine earning. It gives an overview of several asic and advanced topics in machine earning theory. The book is definitely aluable to scientists and engineers who re involved in developing machine learnng tools applied to signal and image proessing applications. This book is also uitable for courses on machine learning nd ...

Pattern Recognition and Machine Learning

In this note, we describe the sequential minimal optimization (SMO) algorithm to solve the soft margin support vector machine (SVM) binary classification problem, which is to be implemented as part of the miniproject. In order to understand our arguments here, the reader is advised to study the SVM chapter of the course notes, in particular the “Solving the Support Vector Machine” section (the ...

Reproducible Research Pattern Recognition and Machine Learning

This is a course on Reproducible Research (RR) [1] for research engineers working with software applications in Pattern Recognition (PR) and Machine Learning (ML) [2]. It motivates and explains concepts behind RR, an increasing trend in scientific publications in this niche, its implications and tools for implementing it on an individual or group levels. It is a hands-on course in the sense stu...