Logo

A Brief Introduction to Machine Learning for Engineers

Large book cover: A Brief Introduction to Machine Learning for Engineers

A Brief Introduction to Machine Learning for Engineers
by

Publisher: arXiv.org
Number of pages: 237

Description:
This monograph aims at providing an introduction to key concepts, algorithms, and theoretical results in machine learning. The treatment concentrates on probabilistic models for supervised and unsupervised learning problems. It introduces fundamental concepts and algorithms by building on first principles, while also exposing the reader to more advanced topics with extensive pointers to the literature, within a unified notation and mathematical framework.

Home page url

Download or read it online for free here:
Download link
(2.1MB, PDF)

Similar books

Book cover: A Course in Machine LearningA Course in Machine Learning
by - ciml.info
Tis is a set of introductory materials that covers most major aspects of modern machine learning (supervised and unsupervised learning, large margin methods, probabilistic modeling, etc.). It's focus is on broad applications with a rigorous backbone.
(14521 views)
Book cover: Machine Learning: The Complete GuideMachine Learning: The Complete Guide
- Wikipedia
Contents: Introduction and Main Principles; Background and Preliminaries; Knowledge discovery in Databases; Reasoning; Search Methods; Statistics; Main Learning Paradigms; Classification Tasks; Online Learning; Semi-supervised learning; etc.
(8093 views)
Book cover: Algorithms for Reinforcement LearningAlgorithms for Reinforcement Learning
by - Morgan and Claypool Publishers
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
(4476 views)
Book cover: The Elements of Statistical Learning: Data Mining, Inference, and PredictionThe Elements of Statistical Learning: Data Mining, Inference, and Prediction
by - Springer
This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.
(33776 views)