sooryamsharma / Machine-Learning-Algorithms

Implemented traditional Machine Learning algorithms such as Decision Trees, Random Forest, Dynamic Time Warping, MDPs & reinforcement learning, KNN, Linear and Logistic Regression, Support Vector Machines (SVM), PCA, SVD, K-means clustering and Naive Bayes classifier on UCI datasets.

Machine-Learning-Algorithms

Implemented various ML algorithms such as:

1. Frequentist Estimate
2. Bayesian Estimate
3. Gaussian Fitting (1D and 2D)
4. Naive Bayes classifier (using Histograms & Mixture of Gaussians)
5. Linear Regression
6. Logistic Regression
7. Neural Networks
8. Decision Trees and Random Forests
9. Principal Component Analysis
10. Singular Value Decomposition
11. Dynamic Time Warping
12. K-nearest neighbor classifiers
13. Dynamic Time Warping
14. K-means clustering
15. MDPs & Reinforcement Learning
16. F-Test (finding 100 prominent features out of 4434 features and then train the classifier using those 100 features).