Computer science study plan.
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TODO Machine Learning

Notes on what goes where

Machine learning practice code goes in a cs/machine-learning repo.

  • Code focused principally on concepts in machine learning,
  • Code uses scikit-learn and other external libraries
  • Fundamental algorithms go in the Python/respective language repo

Repo has a copy on Github, with an HTML landing page. Or, complements circe.

  • HTML landing page with info about each topic.
  • Notebook for each overarching topic.
  • Split into multiple notebooks as needed.
  • Example might be, notebook to compare ridge and lasso.

TODO List

[ ] Bayes Decision Theory

  • 05/25
  • Books:
    • Alpaydin Introduction to Machine Learning
  • Wiki notes:
  • Dimensionality Reduction

  • Regression

  • Regularization

  • Classification

  • Clustering

  • Bayesian

    • Decision Theory
  • Decision Trees

  • Association Rules

  • Neural Networks

  • Deep Learning

  • Regression: linear regression

  • Regression: logistic regression

  • Regression: OLS regression

  • Regression: Stepwise regressoin

  • Regression: MARS

  • Regression: LOESS

  • Instance: k-Nearest Neighbor

  • Instance: Learning Vector Quantization

  • Instance: Self-Organizing Map

  • Instance: Locally Weighted Learning

  • Regularization: Ridge regression

  • Regularization: LASSO

  • Regularization: Elastic net

  • Regularization: LARS

  • Decision Tree: classification tree

  • Decision Tree: CHAID

  • Decision Tree: conditional decision trees

  • Bayesian: LARS

  • Bayesian: Naive Bayes

  • Bayesian: Gaussian Bayes

  • Bayesian: Multinomial Naive Bayes

  • Bayesian: Bayesian Network

  • Bayesian: Bayesian Belief Network

  • Clustering: k-Means

  • Clustering: k-Medians

  • Clustering: Expectation Maximization

  • Clustering: Hierarchical Clustering

  • Dimensionality Reduction: PCA

  • Dimensionality Reduction: t-SNE

  • Dimensionality Reduction: PLS

  • Dimensionality Reduction: Multidimensional Scaling

  • Dimensionality Reduction: Principal Component Regression

  • Dimensionality Reduction: Discriminant Analyses

  • Association Rule: Apriori algorithm

  • Deep Learning: CNN

  • Deep Learning: RNN

  • Deep Learning: LSTM

  • Deep Learning: DBM

  • Deep Learning: DBN

  • Deep Learning: Stacked Auto-Encoders