This book aims at providing an introduction to key concepts, algorithms, and theoretical frameworks in machine learning, including supervised and unsupervised learning, statistical learning theory, probabilistic graphical models and approximate inference. The intended readership consists of electrical engineers with a background in probability and linear algebra.
The treatment builds on first principles, and organizes the main ideas according to clearly defined categories, such as discriminative and generative models, frequentist and Bayesian approaches, exact and approximate inference, directed and undirected models, and convex and non-convex optimization. The text offers simple and reproducible numerical examples providing insights into key motivations and conclusions.
Pages : | /Paperback N/A |
Size : | PDF (206 pages), PostScript. DVI, etc. |
File type : | |
Downloads: | 58 |
Created: | 2020-08-26 |
License: | arXiv.org - Non-exclusive license to distribute |
Author(s): | Osvaldo Simeone |
The Hundred-Page Machine Learning Book
Automated Machine Learning: Methods, Systems, Challenges
Machine Learning for Cyber Physical Systems
An Introduction to Machine Learning, 2nd Edition
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable
This book is a community publication about all things mobile, aims to spread knowledge about mobile technologies and encourage people to enter mobile community or deepen their existing knowledge....
Advances in Flight Control SystemsNonlinear problems in flight control have stimulated cooperation among engineers and scientists from a range of disciplines. Developments in computer technology allowed for numerical solutions of nonlinear control problems, while industrial recognition and applications of nonlinear mathematical mo...
Modern Robotics with OpenCVHow to use a Robot with Computer Vision in order to perform complex tasks, interacting with the surrounding environment, using a distributed system with several software communicating each others and exchanging data across the network....
Intelligence UnleashedDownload free course Intelligence Unleashed, pdf file on 60 pages by Rose Luckin, Wayne Holmes, Mark Griffiths, Laurie B. Corcier....
Getting Started with InnerSourceDownload free course Getting Started with InnerSource, pdf file on 22 pages by Andy Oram....
Skype Bots SuccinctlyDownload free course Skype Bots Succinctly, pdf file on 92 pages by Ed Freitas....
Managed Software EvolutionDownload free course Managed Software Evolution, pdf file on 439 pages by Ralf Reussner, Michael Goedicke, Wilhelm Hasselbring, Birgit Vogel-Heuser, Jan Keim, Lukas Märtin....
LaTeX in 24 HoursDownload free course LaTeX in 24 Hours, pdf file on 309 pages by Dilip Datta....
Perl Notes for ProfessionalsDownload free course Perl Notes for Professionals, pdf file on 108 pages by Stack Overflow Community....
New Applications of Artificial IntelligenceThis book has a complete set of applications of artificial neural networks that allow the reader to gain experience about the new systems for implementing and developing artificial intelligence (AI) methods, which can run in several digital systems. On the other hand, the book shows the newest alg...