This post will further your knowledge in areas that all mathematicians will be interested in. Find out what resources you can read to learn more, and find a selection of useful links including a variety of ebooks, learning platforms, videos, tools and lecture notes on a wide array of topics, such as doing math foundation, set theory, logic, type theory, algebra and many many more.
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.
This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The book is easy to read and only requires a command of one-variable calculus and some very basic knowledge about computer programming.
‘wxMaxima for Calculus I’ and ‘wxMaxima for Calculus II’ introduce the free open-source computer algebra system wxMaxima in the context of single variable calculus. Each book can serve as a lab manual for a one-unit semester calculus lab, a source of supplemental CAS exercises or a tutorial reference for students and instructors who prefer learn computer algebra by example.
This book is about convex optimization, a special class of mathematical optimization problems, which includes least-squares and linear programming problems.
Introduction to Proofs is an undergraduate text. It is Inquiry-Based, sometimes called the Discovery Method or the Moore Method.
This book provides an introduction to the basic principles and tools for the design and analysis of feedback systems. It is intended to serve a diverse audience of scientists and engineers who are interested in understanding and utilizing feedback in physical, biological, information and social systems.
This open access book offers comprehensive coverage on Ordered Fuzzy Numbers, providing readers with both the basic information and the necessary expertise to use them in a variety of real-world applications.
Random number generatlon has intrigued sclentists for a few decades, and a lot of effort has been spent on the creation of randomness on a deterministic (non-random) machlne, that is, on the design of computer algorithms that are able to produce “random” sequences of integers.