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Mathematics for Machine Learning

Mathematics for Machine Learning 9.2分

资源最后更新于 2020-08-23 16:19:00

作者:Marc Peter Deisenroth

出版社:Cambridge University Press

出版日期:2020-01

ISBN:9781108455145

文件格式: pdf

标签: 数学 机器学习 Machine_Learning 人工智能 计算机 2020 英文原版 英国

简介· · · · · ·

https://mml-book.github.io/

::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, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics::

The fundamental mathematical tools needed to under...

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目录

Part I: Mathematical Foundations
Introduction and Motivation
Linear Algebra
Analytic Geometry
Matrix Decompositions
Vector Calculus
Probability and Distribution
Continuous Optimization
Part II: Central Machine Learning Problems
When Models Meet Data
Linear Regression
Dimensionality Reduction with Principal Component Analysis
Density Estimation with Gaussian Mixture Models
Classification with Support Vector Machines