Optimal and Learning Control for Autonomous Robots
by Jonas Buchli, et al.
Publisher: arXiv.org 2017
Number of pages: 101
The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.
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by David J. C. MacKay - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
by Albert Bifet, et al. - The MIT Press
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
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.
by Gianluca Bontempi, Souhaib Ben Taieb - OTexts
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. This manuscript aims to find a good balance between theory and practice.