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Index: Machine Learning

A series on machine learning fundamentals, from nearest neighbors to neural networks, with hands-on experiments and a capstone project.


Articles

  1. K-Nearest Neighbors
    1. K-Nearest Neighbors
    2. Experiment: MNIST Digit Classification
  2. Decision Trees
    1. Decision Trees
    2. Experiment: Heart Disease Prediction
  3. Linear Regression
    1. Linear Regression
    2. Gradient Descent
    3. Experiment: Gradient Descent
    4. Practice Problems
  4. Logistic Regression & Regularization
    1. Logistic Regression and Regularization
  5. Neural Networks
    1. Neural Networks
  6. Backpropagation
    1. Backpropagation
  7. Bias-Variance & Bagging
    1. Bias-Variance Tradeoff and Bagging
  8. Naive Bayes
    1. Naive Bayes
  9. Gaussian Discriminant Analysis
    1. Gaussian Discriminant Analysis

Experiments

  1. Painting Classifier
    1. Experiment: Painting Classifier
    2. Feature Engineering Pipeline
    3. Model Comparison