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
· · · · · · (收起)
具体描述
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 understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
用户评价
##特别适合像我这种已经n年没学过数学的人，也很适合做reference有什么不懂的时候即兴翻翻
评分##part1介绍ml里频繁用到的数学，part2再介绍几个具有代表性的ml算法，知识编排非常合理。 想打十分，感觉很适合拿来入门，但即使是重温（比如我）也会有收获，太喜欢作者的写作风格了。
评分##只读了第一部分的数学基础，快速地过了一遍，还挺不错的
评分##市面上最好的机器学习入门教材（我菜我先说）
评分##不管是拿来入门还是重温都很适合
评分读了数学基础部分，内容不多，但是把一些简单的概念讲得更加透彻，有助于建立数学思维体系
评分读了数学基础部分，内容不多，但是把一些简单的概念讲得更加透彻，有助于建立数学思维体系
评分##虽然很基础，但是对于有些东西经常会给出多种角度的解释，总有一种能让人容易理解和接受，还不错的书，但是如果花太长时间看就比较不值得
评分##市面上最好的机器学习入门教材（我菜我先说）
相关图书
本站所有内容均为互联网搜索引擎提供的公开搜索信息，本站不存储任何数据与内容，任何内容与数据均与本站无关，如有需要请联系相关搜索引擎包括但不限于百度，google,bing,sogou 等，本站所有链接都为正版商品购买链接。
© 2026 windowsfront.com All Rights Reserved. 静流书站 版权所有