UNDERSTANDING REJECTED LOAN APPLICATION ON LENDING CLUB DATA
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Updated
Oct 13, 2024 - Jupyter Notebook
UNDERSTANDING REJECTED LOAN APPLICATION ON LENDING CLUB DATA
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.
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.
Exploring anomaly detection using unsupervised methods in scikit-learn
K means implementation from scratch
Crosslingual Information Retrieval on the europarl dataset.
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
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