/Stanford_CS229.Machine_Learning

Linear classifiers (Logistic Regression, GDA), Stochastic Gradient Descent, L1 L2 Regularization, SVM

Primary LanguageJupyter Notebook

Machine Learning [Stanford/CS229]

http://cs229.stanford.edu/syllabus-autumn2018.html

Problem Sets

This repo contains all the Problem Sets of CS229, which includes Mathematical and Programming projects.

PS-Summary

Machine Learning Knowledge Sharing

See more about Machine Learning and Data Science in general. ML_Guidance_Repo

Classification of Algorithm

  • Continuous
Unsupervised * Supervised *
Clustering & Dimensionality Reduction Regression
○ SVD ○ Linear/Polynomial
○ PCA Decision Trees
○ K-means Random Forest
  • Discrete (Category)
Unsupervised Classification
Association Analysis ○ KNN/ Trees
○ Apriori ○ Logistic Regression
○ FP-Growth ○ Naive Bayes
Hidden Markov Model ○ SVM

Library

Numpy, matplotlib, pandas, TensorFlow

Caffe, Keras

XGBoost, gensim