This document is an attempt to provide a summary of the mathematical background needed for an introductory class in machine learning, which at UC Berkeley is known as CS 189/289A.
The Teach Yourself Logic Study Guide aims to provide the needed advice by suggesting some stand-out books on various areas of mathematical logic.
This book is based on an honors course in advanced calculus that we gave in the 1960’s. It can accordingly be used (with omissions) as a text for a year’s course in advanced calculus, or as a text for a three-semester introduction to analysis.
This easy-to-read book introduces the basics of solving partial differential equations by means of finite difference methods. Unlike many of the traditional academic works on the topic, this book was written for practitioners.
This Special Issue on Real-Time Optimization includes both methodological and practical contributions. All seven methodological contributions deal with explicit RTO schemes that repeat the optimization when new measurements become available.
Maxima by Example is a series of tutorial notes which include many examples of the power of Maxima. Designed for the new user, we include some “nuts and bolts” suggestions for working with the Maxima software, especially for the Windows user.
It is intended for a student who, while not yet very familiar with abstract reasoning, is willing to study more rigorous mathematics that is presented in a “cookbook style” calculus type course.
This text contains sufficient material for a one-semester course in mathematical algorithms, for second year mathematics students. The course requires some exposure to the basic concepts of discrete mathematics, but no computing experience.
This is a calculus textbook at the college Freshman level based on Abraham Robinson’s infinitesimals. Robinson’s modern infinitesimal approach puts the intuitive ideas of the founders of the calculus on a mathematically sound footing, and is easier for beginners to understand than the more common approach via epsilon, delta definitions.