A Course in MacHine Learning

By Daumé, Hal

Book Id: WPLBN0003842795
Format Type: PDF eBook :
File Size:
Reproduction Date: 2015

Title:	A Course in MacHine Learning
Author:	Daumé, Hal
Volume:
Language:	English
Subject:	MacHine Learning, Ai and Robotics, Programming
Collections:	Online Programming Books
Historic Publication Date:	2014
Publisher:	Todo


Citation APA MLA Chicago Haldaumé,. (2014). A Course in MacHine Learning. Retrieved from http://gutenberg.cc/

Description
Description: Topics covered include: decision trees, geometry and nearest neighbors, the perceptron, machine learning in practice, beyond binary classification, linear models, probabilistic modeling, neural networks, kernel methods, learning theory, ensemble methods, efficient learning,,unsupervised learning,,expectation maximization, semi-supervised learning, graphical models, online learning, structured learning and bayesian learning. Hal Daumé III is an Assistant Professor in Computer Science at the University of Maryland.

Table of Contents
TOC : Decision Trees - Geometry and Nearest Neighbors - The Perceptron - Practical Issues - Beyond Binary Classification - Linear Models - Probabilistic Modeling - Neural Networks - Kernel Methods - Learning Theory - Ensemble Methods - Efficient Learning - Unsupervised Learning - Expectation Maximization - Semi-Supervised Learning - Graphical Models - Online Learning - Structured Learning Tasks - Bayesian Learning.