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10 search results found

Anomaly Detection Resources ⭐ 7,616

Anomaly detection related books, papers, videos, and toolboxes

Sealion ⭐ 328

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

Machine Learning Algorithms From Scratch ⭐ 312

Implementing machine learning algorithms from scratch.

A stable algorithm for GAN training

Labelpropagation ⭐ 101

A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).

Fast and explainable clustering in Python

Sutton Barto Rl Exercises ⭐ 83

📖Learning reinforcement learning by implementing the algorithms from reinforcement learning an introduction

Online Category Learning ⭐ 56

ML algorithm for real-time classification

Fast Kmeans ⭐ 50

Code to speed up k-means clustering. Originally at BaylorCS/baylorml.

machine learning algorithms in Swift

DBSCAN Clustering Algorithm C# Implementation

Conditional Associative Logic Memory

Kmedoids ⭐ 23

The Partitioning Around Medoids (PAM) implementation of the K-Medoids algorithm in Python [Unmaintained]

A simple implementation of K-means (and Bisecting K-means) clustering algorithm in Python

Handson Unsupervised Learning With Python ⭐ 14

HandsOn-Unsupervised-Learning-with-Python, Published by Packt

Python implementation of factorization based image segmentation algorithm

Machine Learning Course ⭐ 13

Machine Learning Course @ Santa Clara University

Code to do blind source separation with more microphones than sources using auxilliary based independent vector analysis.

Votermla ⭐ 10

Machine Learning Algorithms used to predict which candidate a county voted for based on 9 distinct attributes such as population size and density

Algo Week ⭐ 8

Dual Process Reinforcement ⭐ 8

An intelligent agent that adaptively changes its thought processes to maximize cumulative reward

Image Mimic Genetic Algorithm ⭐ 7

This unsupervised genetic algorithm i have created will try to mimic the target image (New random image will be generated at each time)

Gpu Cuda Self Organising Maps ⭐ 7

🧠 💡 📈 A project based in High Performance Computing. This project was built using CUDA (Compute Unified Device Architecture), C++ (C Plus Plus), C, CMake and JetBrains CLion. The scenario of the project was a GPU-based implementation of the Self-Organising-Maps (S.O.M.) algorithm for Artificial Neural Networks (A.N.N.), with the support of CUDA (Compute Unified Device Architecture), using its offered parallel optimisations and tunings. The final goal of the project was to test the several GPU

Machine Learning Algorithm ⭐ 7

Some algorithms of machine learning like Regression, Cluster, Deep Learning, and much more.

This package is used to calculate the Strain Elevation Tension Spring embedding (SETSe) for networks in R

Change Detection Pca Kmeans ⭐ 5

Unsupervised Change Detection Algorithm using PCA and K-Means Clustering

K Means Image Compression ⭐ 5

Using K-means Clustering for Image Compression

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