Remote Sensing Data Analysis in R 🛰

Sentinel-2 Leaf Area Index Estimation for Pine Plantations in the Southeastern United States

Emotion recognition from Speech & Text using different heterogeneous ensemble learning methods

Minimax Classification with 0-1 Loss and Performance Guarantees

Détecter les faux billets à partir du jeu de données englobant statistiques sur 6 caracthéristiques des billets

A Time-Series Analysis on the Urban Growth of Denver since 1986. This project utilizes Google Earth Engine in conjunction with the geemap package developed by Dr. Quisheng Wu. Supervised classification was conducted on Landsat images of the greater Denver Metro area and corroborated with Census data to analyze the growth of Denver's urban center…

This Machine Learning repository encompasses theory, hands-on labs, and two projects. Project 1 analyzes customer segmentation for marketing using clustering, while Project 2 applies supervised classification in marketing and sales.

Exploratoy Data Analysis,Logistic Regression,Penalized Logistic Regression (LASSO), LDA, Decision Trees, Bagging, Random Forest

Code for predicting the severity of earthquake impact on buildings through various experiments, utilizing models like Logistic Regression, SVM, XGBoost, Neural Networks, and Random Classifier. It employs Grid Search and Randomized Search for optimal configuration and relies on feature correlations as primary predictors, adjustable with a threshold.

This repository includes all the scripts developed during the Final Degree Project aiming to provide new insights in risk stratification of Brugada Sindrome through AI-based approaches.

Repositorio creado para mi primer proyecto de Machine Learning, hecho durante mi tiempo en el bootcamp de Data Science de The Bridge. Estudio sobre la calidad del agua, con aprendizaje supervisado

Detecting deforestation in the Brazilian Amazon by using NDVI and Woodiness index

To Predict Credit Risk with Supervised Machine Learning.

Exam project of Data Technology and Machine Learning course @unimib18/19.

Understanding and predicting the factors leading to employees leaving and finding relations between them. Also finding the importance of a feature according to ML models.

Supervised ML to classify gender of redditors based on messages and threads. Used mostly pandas and SciKitLearn

Mangrove Ecosystem Mapping Using Multisumber Images (Sentinel-2A and Sentinel-1) Using Cloud-Based Computing In Balikpapan Bay in 2019 and 2022.

R package (R6 class) based on a Gaussian Naive Bayes for supervised classification

A simple convolutional neural network (CNN) to classify ten different types of leaf diseases in tomatoes using Deep Learning frameworks and libraries.