Mathematics for Machine Learning

Understanding Machine Learning (Shai Shalev-Shwartz,Shai Ben-David)(Pevná)

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ide...

Quantum Machine Learning with Python (Brožovaná)

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particl...

Quantum Machine Learning with Python

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particl...

Mathematics of Machine Learning

Mathematics of Machine Learning

Mathematics for Machine Learning (Marc Peter Deisenroth,A. Aldo Faisal,Cheng Soon Ong)(Brožovaná)

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses

Mathematics for Machine Learning

This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, an

Mathematics for Machine Learning

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses

Exercises in Applied Mathematics

This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections.  It explores essential tools from linear algebra, elementary functional analysis, and proba...

Introduction to Deep Learning

This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the m...