140 Machine Learning Formulas

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本帖隐藏的内容

By Rubens Zimbres. Rubens is a Data Scientist, PhD in Business Administration, developing Machine Learning, Deep Learning, NLP and AI models using R, Python and Wolfram Mathematica. Click here to check his Github page.

Extract from the PDF document

This is a 17 page PDF document featuring a collection of short, one-line formulas covering the following topics (and more):

• Naive Bayes
• Mixture Models
• EM Algorithm
• Maximum Likelihood
• Bayesian Networks
• k-NN, weighted NN
• Logistic Regression
• Principal Component Analysis
• Stochastic Gradient
• Neural Networks
• Collaborative Filtering
• Back Propagation
• Support Vector Machines
• Ridge and Lasso Regression
  

It does look like a cheat sheet with everything you need to know in terms of formulas used in standard machine learning algorithms. It would be helpful if someone could add some meat to this document, in particular, adding some context and explanations for each formula. Many of these formulas are nicely illustrated here (scroll to the bottom of the page after clicking on the link.)

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关键词：formulas Learning machine earning Formula

kankan

thanks for sharing

duoxie                                    

谢谢分享

140 Machine Learning Formulas

thanks for sharing

140 Machine Learning Formulas