/Master-Machine-Learning

Implement common statistical machine learning algorithms with raw Numpy.

Primary LanguageJupyter Notebook

Master Statistical Machine Learning

implement common statistical machine learning algorithms with raw Numpy.

The code is undergoing the first review.

  • 0.kNN arithmetic

    • kNN arithmetic
    • kNN algorithm using kdd tree

  • 1.Linear Model

    • Linear Regression
    • Logistic Regression
    • Multi-layer Perceptron Regressor

  • 2.Tree Model

    • ID3 Classification Tree
    • Classification and Rgression Tree

  • 3.Support Vector Machine

    • Solving Linear SVM with Scipy
    • Solving linear SVM using SMO
    • Support Vector Regression

  • 4.Master Feature Engineering

    • Basic Feature Engineering
    • Advanced Feature Engineering

  • 5.Ensemble Methods

    • Adaboost
    • GBDT
    • RandomForest
    • XGBoost
    • Model stacking

  • 6.Unsupervised Learning

    • K-menans
    • PCA

  • 7.Bayesian Machine Learning

    • Naive Bayes
    • Bayesian Linear Regression
    • Gaussian Mixture Model
    • Hidden Markov Model
    • Conditional Random Field
    • Latent Dirichlet Allocation