Python code for common Machine Learning Algorithms

Python library for portfolio optimization built on top of scikit-learn

A Julia package for data clustering

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见机器学习算法原理与实现

Social Network Analysis and Visualization software application.

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets.

A Python implementation of divisive and hierarchical clustering algorithms. The algorithms were tested on the Human Gene DNA Sequence dataset and dendrograms were plotted.

Learning M-Way Tree - Web Scale Clustering - EM-tree, K-tree, k-means, TSVQ, repeated k-means, bitwise clustering

Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch (NeurIPS 2021)

Algorithms and evaluation tools for extreme clustering

A fast approximation to a Dirichlet Process Mixture model (DPM) for clustering genetic data

Genie: Fast and Robust Hierarchical Clustering with Noise Point Detection - in Python and R

Browser-based visualization tool that uses JSON and an interactive enclosure diagram to visualize networks.

Machine Learning Library, written in J

machine learning algorithms in Swift

Official PyTorch Implementation of HIER: Metric Learning Beyond Class Labels via Hierarchical Regularization, CVPR 2023

A hierarchical agglomerative clustering (HAC) library written in C#

Hierarchical divisive clustering algorithm execution, visualization and Interactive visualization.

Interactively and visually explore large-scale image datasets used in machine learning using treemaps. VIS 2022