The goal of this project is to identify students at risk of dropping out the school

成信助手相关源代码（成信好老师，成信贴吧大数据，成信曝光台，成信新闻）

Color Quantization using K-Means(Machine learning)

Detecting Fake User Profiles using k-Means and Local Outlier Factor

Repository for the "Fundamentos del Aprendizaje Automático" subject

Detects human activity by supervised and unsupervised methods same as SVM, Logistic Regression, Neural Networks, K-means, GMM and compares results

Analyse de données et classification supervisée et non supervisée

Applied unsupervised learning techniques on demographic and spending data for a sample of German households.

This course content includes that Classification(Supervised Method:),Clustering(Unsupervised Method),Association Analysis.

Recommendation of similar images to the given image using ResNet50, K-Means and cosine similarity.

Full Flask - BI application used for segmentation - machine learning

Customer loyalty program for E-commerce. Feel free to access the report in the link below.

K-means Clustering implementation on random points in 2D plane

A Flask web application that extracts dominant colors from uploaded images.

Facilitating deep phenotyping by automating the screening of case studies & the comparison of patient similarities (through clustering). This can be used to get an understanding of the underlying pathophysiology for a rare genetic disorder.

Applying data mining techniques to a set of documents to determine meaningful relationships between them.

Customer Segments - Machine Learning Nanodegree from Udacity

Use the credit card customer database to segement the groups by taking into account their spending patterns as well as past interactions with the bank

(Work in progress) Repository for some machine learning procedures used in multiple scenarios.