Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)

Learning Bayesian Network parameters using Expectation-Maximisation

Python implementation of a complex-valued version of the expectation-maximization (EM) algorithm for fitting Gaussian Mixture Models (GMMs).

Machine Learning From Scratch

Implementation of Task-Parameterized-Gaussian-Mixture-Models as presented from S. Calinon in his paper: "A Tutorial on Task-Parameterized Movement Learning and Retrieval"

Image Segmentation with Expectation Maximization Algorithm and Gaussian Mixture Models from scratch in Python

Various machine learning projects using public datasets

Quasi Deterministic extension to the hidden Markov model for time-series and sequence modelling.

Implementation of the Expectation Maximization Algorithm for Hidden Markov Models including several Directional Distributions

Performed text preprocessing, clustering and analyzed the data from different books using K-means, EM, Hierarchical clustering algorithms and calculated Kappa, Consistency, Cohesion or Silhouette for the same.

The implementation of mixtures for different tasks.

Python code to fit Gaussian Mixture Models to data using expectation maximization

Hidden Markov Random Field Model and its Expectation-Maximization

Find Clusters of data using Expectation Maximization algorithm on mixture of gaussians

Expectation-Maximization (EM) algorithm for Gaussian mixture model (GMM) from scratch

Sample efficient learning using expectation maximization

Write a code to implement Fuzzy Clustering with EM (Expectation Maximization) algorithm for clustering

A comparative study between 5 different binary classification techniques.