机器学习相关的数学

机器学习
机器学习


1、机器学习中的数学 (ucsc.edu)

http://people.ucsc.edu/~praman1/static/pub/math-for-ml.pdf


机器学习数学基础(UMIACS CMSC422)

http://www.umiacs.umd.edu/~hal/courses/2013S_ML/math4ml.pdf


2、线性代数

线性代数简明指南(betterexplained.com)

http://betterexplained.com/articles/linear-algebra-guide/


码农眼中矩阵乘法 (betterexplained.com)

http://betterexplained.com/articles/matrix-multiplication/


理解叉乘运算(betterexplained.com)

http://betterexplained.com/articles/cross-product/


理解点乘运算(betterexplained.com)

http://betterexplained.com/articles/vector-calculus-understanding-the-dot-product/


机器学习中的线性代数(U. of Buffalo CSE574)

http://www.cedar.buffalo.edu/~srihari/CSE574/Chap1/LinearAlgebra.pdf


深度学习的线代小抄(medium.com)

http://medium.com/towards-data-science/linear-algebra-cheat-sheet-for-deep-learning-cd67aba4526c


复习线性代数与课后阅读材料(Stanford CS229)

http://cs229.stanford.edu/section/cs229-linalg.pdf


3、概率论

贝叶斯理论 (betterexplained.com)

http://betterexplained.com/articles/understanding-bayes-theorem-with-ratios/


理解贝叶斯概率理论(Stanford CS229)

http://cs229.stanford.edu/section/cs229-prob.pdf


复习机器学习中的概率论(Stanford CS229)

http://see.stanford.edu/materials/aimlcs229/cs229-prob.pdf


概率论(U. of Buffalo CSE574)

http://www.cedar.buffalo.edu/~srihari/CSE574/Chap1/Probability-Theory.pdf


机器学习中的概率论(U. of Toronto CSC411)

http://www.cs.toronto.edu/~urtasun/courses/CSC411_Fall16/tutorial1.pdf


4、计算方法(Calculus)

如何理解导数:求导法则,指数和算法(betterexplained.com)

http://betterexplained.com/articles/how-to-understand-derivatives-the-quotient-rule-exponents-and-logarithms/

如何理解导数,乘法,幂指数,链式法(betterexplained.com)

http://betterexplained.com/articles/derivatives-product-power-chain/

向量计算,理解梯度(betterexplained.com)

http://betterexplained.com/articles/vector-calculus-understanding-the-gradient/

微分计算(Stanford CS224n)

http://web.stanford.edu/class/cs224n/lecture_notes/cs224n-2017-review-differential-calculus.pdf

计算方法概论(readthedocs.io)

http://ml-cheatsheet.readthedocs.io/en/latest/calculus.html

需要全部视频、高清课件、作业的同学可以在公众号后台回复“课程”!

或者加客服好友!

标签
推荐