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: An Introductory Study on Time Series Modeling and ForecastingAn Introductory Study on Time Series Modeling and Forecasting
by - arXiv
This work presents a concise description of some popular time series forecasting models used in practice, with their features. We describe three important classes of time series models, viz. the stochastic, neural networks and SVM based models.
(14037 views)
Book cover: An Introduction to Statistical LearningAn Introduction to Statistical Learning
by - Springer
This book provides an introduction to statistical learning methods. It contains a number of R labs with detailed explanations on how to implement the various methods in real life settings and it is a valuable resource for a practicing data scientist.
(12041 views)
Book cover: Introduction to Machine Learning for the SciencesIntroduction to Machine Learning for the Sciences
by - arXiv.org
This is an introductory machine learning course specifically developed with STEM students in mind, written by the theoretical Condensed Matter Theory group at the University of Zurich. We discuss supervised, unsupervised, and reinforcement learning.
(5058 views)
Book cover: Introduction To Machine LearningIntroduction To Machine Learning
by
This book concentrates on the important ideas in machine learning, to give the reader sufficient preparation to make the extensive literature on machine learning accessible. The author surveys the important topics in machine learning circa 1996.
(32853 views)