Subnational Cholera Analysis in Yemen
Analisis korelasi, analisis faktor, dan PCA pada Dataset Modis (titik api) di Peru tahun 2010-2015 sebagai tugas Mata Kuliah Data Mining
Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervise…
Applying unsupervised learning algoriths on online shoppers intention data and model building
R project on high-dimensional data analysis with PCA, hierarchical clustering, and k-means
This repository includes my project to cluster the Mexican provinces/states based on a development model that I developed using several social and economic indicators.
En este repositorio se encuentra el Trabajo de Fin de Máster de la Titulación Máster en Ciencia de Datos por la Universitat Oberta de Catalunya.
Analyze school districts' electric school bus adoption using unsupervised learning to find patterns in socio-economic and environmental factors.
Learn main contents ML
Transversal project in R: Biostatistical análisis applied to genetic expression
CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins
A machine learning project that classifies facial emotions (happy vs. neutral) using Principal Component Analysis for feature extraction and Support Vector Machine for classification.
🎯 Unsupervised learning pipeline to identify target customer segments from German demographics data using PCA and K-Means clustering.
Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
Some introductory data science projects, along with code and documentation. Of course, these projects are university projects.
Étude statistique multidimensionnelle des polluants atmosphériques et facteurs météo à Périgueux via Analyse en Composantes Principales (ACP) sous R.
Case study for dataset (Violence in USA, 90`). Combination of socio-economic data with FBI stats. Models: PCA, Clustering, Multiple regression. Methodology CRISP DM
Udacity Nanodegree Project 3: Example of unsupervised learning. Creating customer segments.
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