A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)

螺旋熵减系统

AAAI 2018 - Unsupervised video summarization with deep reinforcement learning (Theano)

螺旋熵减理论

pyMCR: Multivariate Curve Resolution for Python

Self-organizing maps in Go

This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima

The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.

Stanford Online course STATSX0001 "Statistical Learning" follows closely the sequence of chapters in the course text "An Introduction to Statistical Learning, with Applications in R" (James, Witten, Hastie, Tibshirani - Springer 2013). Trevor Hastie Professor of Statistics and of Biomedical Data Sciences, Stanford University, and Robert Tibshirani Professor of Biomedical Data Science and Statistics, Stanford University

unsupervised learning of natural images -- à la SparseNet.

No description provided.

GRASPED: A GRU-AE Network based Multi-perspective Business Process Anomaly Detection Model

Adaptive Common Spatio-Temporal Pattern (ACSTP) for Event-Related Potential (ERP) analysis.

This repository contains practical implementations of core machine learning algorithms and techniques, created for learning and practice purposes.

This repository contains machine learning programs in the Python programming language.

It consists of basic concepts of Machine-Learning with its algorithms.

Applying pre-trained CNN and clustering algorithms on recognizing people in videos

Unsupervised ensemble learning methods for time series forecasting. Bootstrap aggregating (bagging) for double-seasonal time series forecasting and its ensembles.

This Repository Consists All Courses, Projects and Online Learning Done in Context of Machine learning, Data Sceince And Deep Learning From Various Sources like Youtube, Coursera, Udemy And WEbsites like Scikit, Keras

Hear All Solution In R Language

Basic templates of codes for quick ML

Complete lecture slides for Machine Learning (ES-442) at GIK Institute, Fall 2025. Covers Supervised Learning (Decision Trees, SVM, Neural Networks), Unsupervised Learning (Clustering, SOM), and Reinforcement Learning (MDPs, Q-Learning, Deep RL).

Unsupervised Learning (PCA) on Vehicle dataset

Python3 implementation of the Unsupervised Deep Learning Algorithm, Restricted Boltzmann Machine.

Improving jet clustering using different unsupervised learning algorithms

Clustering Algorithms (KMeans, MeanShift, (Merged KMean and MeanShift) and DBSCAN)

Unsupervised Learning Project of Udacity Data Scientist Nanodegree

Implementation of various Machine Learning models

Implementation of K-Means clustering algorithm in python

This repository holds my completed Octave/Matlab code for the exercises in the Stanford Machine Learning course, offered on the Coursera platform.