Logo

Statistical Foundations of Machine Learning

Small book cover: Statistical Foundations of Machine Learning

Statistical Foundations of Machine Learning
by


Number of pages: 269

Description:
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. In particular, we focus on supervised learning problems, where the goal is to model the relation between a set of input variables, and one or more output variables, which are considered to be dependent on the inputs in some manner.

Download or read it online for free here:
Download link
(7MB, PDF)

Similar books

Book cover: Machine Learning and Data Mining: Lecture NotesMachine Learning and Data Mining: Lecture Notes
by - University of Toronto
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.
(6033 views)
Book cover: A Survey of Statistical Network ModelsA Survey of Statistical Network Models
by - arXiv
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(4397 views)
Book cover: The Hundred-Page Machine Learning BookThe Hundred-Page Machine Learning Book
by
This is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
(2099 views)
Book cover: Lecture Notes in Machine LearningLecture Notes in Machine Learning
by - Central Connecticut State University
Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning ...
(5884 views)