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Machine Learning

This repository includes my understanding of some ideas in machine learning

The first part ---> The study of Machine Learning in Action

Classification

  1. C2_KNN

  2. C3_Trees

  3. C4_Bayes

  4. C5_LogisticRegression

  5. C6_SVM

  6. C7_AdaBoost

Prediction

  1. C8_Regression

  2. C9_CART

Unsupervised Learning

  1. C10_K-means

  2. C11_Apriori

  3. C12_FP-growth

Compelmentary tools

  1. C13_PCA

  2. C14_SVD

The second part ---> The study of Coursera--Machine Learning by Andrew Ng

  1. Linear Regression

  2. Logistic Regression

  3. Multi-class Classification and Neural Networks

  4. Neural Networks Learning

  5. Regularized Linear Regression and Bias v.s. Variance

  6. Support Vector Machines

  7. K-means Clustering and Principal Component Analysis

  8. Anomaly Detection and Recommender Systems

The third part ---> The study of Computer Vision (CS231N) by Fei-Fei Li

A1-1 KNN

A1-2 SVM

A1-3 Softmax

A1-4 FCN

A2-1 BN

A2-2 Dropout

A2-3 SGD with Momentum

A2-4 CNN

A3-1 RNN

A3-2 LSTM

A3-3 Generating Captions