这份手册最大的特点就是包含许多关于机器学习的经典公式和图表,有助于您快速回忆有关机器学习的知识点。非常适合那些正在准备与机器学习相关的工作面试的人。
项目地址:
https://github.com/soulmachine/machine-learning-cheat-sheet
该手册虽然只有 135 页,但麻雀虽小五脏俱全,包含了 28 个主题内容,目录如下:
Introduction
Probability
Generative models for discrete data
Gaussian Models
Bayesian statistics
Frequentist statistics
Linear Regression
Logistic Regression
Generalized linear models and the exponential family
Directed graphical models(Bayes nets)
Mixture models and the EM algorithm
Latent linear models
Sparse linear models
Kernels
Gaussian processes
Adaptive basis function models
Hidden markov Model
State space models
Undirected graphical models(Markov random fields)
Exact inference for graphical models
Variational inference
More variational inference
Monte Carlo inference
Markov chain Monte Carlo (MCMC)inference
Clustering
Graphical model structure learning
Latent variable models for discrete data
Deep learning
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