Recognition of Persomnality Types from Facebook status using Machine Learning
The analysis and classification of sleep, cardiovascular metrics, and lifestyle factors, for close to 400 fictive persons aiming to identify whether a potential client is likely to have a sleep disorder.
Sub-seasonal temperature and heatwave prediction in Central Europe with AI (linear and random forest machine learning models)
A Real Time Expression Detector using Python and Machine Learning
Analysis of the Avila bible dataset from the UCI repository using several machine learning algorithms.
Multilable fast inference classifiers (Ridge Regression and MLP) for NLPs with Sentence Embedder, K-Fold, Bootstrap and Boosting. NOTE: since the MLP (fully connected NN) Classifier was too heavy to be loaded, you can just compile it with the script.
Self-study ML project: salary & performance prediction app using an HR productivity dataset
This repository serves as a platform to upload new code updates for my Master's Thesis (TFM), focused on the utilization of both supervised and unsupervised models on a dataset extracted from Spotify. It also includes a small fragment of my thesis. For more information, please contact me at:
Fall 2020 - Computational Medicine - course project
Detecting Fraud Transactions using the Credit Card Fraud Detection dataset
Revolutionary AI-powered anemia detection platform combining browser-based ML (98.75% accuracy) with Gemini AI. Features intelligent temporal analysis comparing past vs current blood reports to track health progression, enabling early intervention for 3 billion at-risk individuals globally.
This repository contains my solution for the Spaceship Titanic Kaggle competition. The objective is to predict which passengers were transported to an alternate dimension using machine learning models.
We prepare a machine learning model that can be used to propose potential novel effective drugs to fight SARS-CoV-2, the virus responsible for COVID-19.
This project focuses on analysing the performance of various Machine Learning models available in python's scikit-learn package when trying to predict wine classification.
Predicting Bank Credit Card Customer Churn using the Credit Card Customers dataset.
Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.
Project for the ING Lion's Den Competition. The goal of this project is to predict defaults of Big Lion Bankβs customers and I build logit, ridge, KNN and XGBoost models.
Predicting the Grade of the damage using multiple features to take the necessary precautions
Source code for Cyber-Attack Monitoring and Detection using Machine Learning Techniques paper
π Analyze how lifestyle factors impact sleep quality and duration using real data to uncover insights that could enhance sleep health.
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