The project is mainly to demonstrate the performance in terms of convergence for Random Initialisation and K++ for K-Means Algorithm.

Natural Language Processing to predict future words in text prediction app

This repository if for creating auto-encoders easily. The main focus of the auto-encoders on this page is for genetic and spectral data analysis but likely could be used for any high dimensional data

Repositori ini berisi dua project analisis data menggunakan metodologi CRISP-DM. Project pertama meneliti tren penjualan Walmart dengan Supervised analysis menggunakan algoritma Naive Bayes Gaussian dan K-Nearest Neighbors. Project kedua mengeksplorasi faktor sosio-ekonomi antar negara dengan Unsupervised analysis.

"Sentiment Analysis of tweets about Covid-19 based on geolocation"

Grabcut implementation, which is color-based foreground-background segmentation. It's based on my 2011 uni project but rewritten and improved.

K means implementation from scratch

Crosslingual Information Retrieval on the europarl dataset.

This is the implementation of SIGIR - 2005 paper on Iterative translation disambiguation for cross-language information retrieval

Artificial Intelligence: Apply the principles of Unsupervised Learning.

The project involves building models for scoring & segregating users acccording to certain threshold criteria based on features from LinkedIn on threshold criteria-refer ReadMe.

Implementation of the Apriori algorithm for finding frequent sets for association rule mining

无监督说话人聚类算法比较

This is a code implementation of the paper Invariant Information Clustering for Unsupervised Image Classification and Segmentation

In this project the Turkey Student Evaluation dataset which in question consists of feedback from students who attended multiple courses at Gazi University, Ankara used.To analyze the questions we used unsupervised learning methods, which involve finding patterns or groupings in a given dataset without any labeled output variable.

VQ-VAE for Acoustic Unit Discovery and Voice Conversion

Unsupervised Machine Learning - Clustering

Comparison of various distance metrics used in clustering techniques for unsupervised learning

Brain Tumor Detection using Color Segmentation with KMeans Clustering ⚠️