Machine Learning Algorithms implemented in Python with numpy for vectorization, and matplotlib for visualization.

1. Supervised learning Algorithms : 

  1. Linear Regression
  2. Logistic Regression
  3. Back propagation
  4. All algorithms currently use Gradient Descent as optimization routine. All algorithms are regularized to avoid overfitting.

2. Unsupervised learning:

  1. Dynamic Time Warping
  2. KMeans Clustering
  3. Gaussian Mixture Model with Expectation Maximization algorithm
  4. Principal Component Analysis

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4 Comments

This seems to be an interesting project Umanga...Thanks for the code and material.
5 years, 4 months ago

Nice implementation in Python. Great Job
5 years, 4 months ago

what is the clustering algorithm for the above clusters?is that for the bilinear feature ,what is the relation of the observation with the clustering?
5 years, 4 months ago

thanks everyone @binod, i have implemnted 2 c clustering algorithm for the above clustering algorithms..... K means nad Gaussian Mixture model.... the computation works for any dimensional feature.... but visualization is only for 2d features...
5 years, 4 months ago

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