Shed Skin is a restricted-Python-to-C++ compiler. Read the introduction below to learn about the restrictions.

detroit is a Python implementation of d3js

Yet another Python Python

Python implementation of popular machine learning algorithm

[ICLR 2023] ReScore: Boosting Causal Discovery via Adaptive Sample Reweighting

An neural network to classify the handwritten digits 0-9 for the MNIST dataset. No NN/ML libraries used.

A python implementation for computing the Hopkins' statistic (Lawson and Jurs 1990) for measuring clustering tendency of data

This repository provides a comprehensive machine learning course with theoretical concepts and practical implementations

detroit-live is based on detroit and aims to bring interactivity to visualizations.

A Python implementation of a binary text classifier using Doc2Vec and SVM.

The python interpreter implemented in Rust (WIP)

Python implementation of Apriori Algorithm from scratch for finding frequent item sets

Patch block img files with <Partition>.patch.dat, like OTA zip but on any devices which could run Python3.13 | imgpatchtools Project Python3 Implementation.Generated by deepwiki ai

[JOURNAL TIP] 004 - Python With Clang

Répertoire Python pour le codage Huffman. Comprend des fonctions d'encodage et de décodage, ainsi qu'une classe Noeud pour la construction de l'arbre de Huffman. Facile à utiliser avec une licence MIT.

evaluation metrics implementation in Python from scratch

A Python implementation of a binary text classifier using Word2Vec and SVM.

This is the repository for our group project for Discrete Maths course. Our topic was famous travelling salesman problem.

Transpose operator

Tranpose operator

End-to-End Python implementation of Semantic Divergence Metrics (SDM) for LLM hallucination detection. Uses ensemble paraphrasing, joint embedding clustering, and information-theoretic measures (JSD, KL divergence, Wasserstein distance) to quantify prompt-response semantic consistency. Based on Halperin (2025).

k-Nearest Neighbors Algorithm with p-adic Distance

This repository provides a comprehensive machine learning course with theoretical concepts and practical implementations

This is a project that implements the K-Nearest Neighbors (KNN) algorithm in Python. KNN is a machine learning algorithm used for classification or regression based on training data, and is an unsupervised learning model. This implementation allows you to train a KNN model on training data and classify new data.

Contains the architecture of neural network in python (without using any framework)

This project is an implementation of Principal Component Analysis (PCA) in Python. PCA is a technique for dimensionality reduction and data visualization that aims to find the most important underlying patterns in a dataset.

This repository contains implementations of linear regression using both gradient descent and linear algebra techniques. The goal of these implementations is to provide a thorough understanding of the linear regression algorithm and its various approaches to solving for the optimal model parameters.

This repository contains an implementation of the K-Means clustering algorithm in Python. K-Means is an unsupervised machine learning algorithm that finds clusters in an N-dimensional space. The implementation provided in this repository allows users to apply K-Means to their own data sets and visualize the resulting clusters.

This repository includes both description and implementation of all 23 design patterns

(Adkins & Paxson) Analytical Method Modelling on Sequential Investment Opportunites for Project Valuations.