galdamour / machine-learning

Python machine learning applications in image processing and algorithm implementations including Gaussian Mixture Model, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, K Nearest Neighbors, K Means, Naive Bayes, Gaussian Discriminant Analysis, Newton Method, Gradient Descent

Machine Learning

Intro

You never truly understand how a wheel works until you reinvent it.
--- T.M.

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Algorithms

1. Gradient Descent (Batch/Stochastic)

2. Newton Method for Logistic Regression

3. Gaussian Discriminant Analysis

4. Naive Bayes (Multivariate/Multinomial/KL Divergence)

5. Support Vector Machine (Binary/Multiclass/DAG/SMO)

6. Decision Tree/Random Forest

7. K Means

8. K Nearest Neighbors

9. DBSCAN

10. Gaussian Mixture Model

Applications

1. Reverse Engineering project