Notebooks for Kaggle competition

This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.

Detecting brain age based on MRI scans data.

Dynamically adjust cost of the rides in response to changing factors

Accident damage prediction using catboost regressor

Linking Writing Processes to Writing Quality

Math Score Predictor

Estimating abalone rings (age) based on their physical characteristics, such as gender, length, height, diameter, weight, etc.

This project aims to predict flight arrival delays using various machine learning algorithms. It involves EDA, feature engineering, and model tuning with XGBoost, LightGBM, CatBoost, SVM, Lasso, Ridge, Decision Tree, and Random Forest Regressors. The goal is to identify the best model for accurate predictions.

A light-weight Kaggle challenge to predict crabs' age

Predicting house prices using advanced regression algorithms

Predicting house prices using advanced regression techniques (LightGBM, XGBoost, CatBoost, stacking) on Kaggle’s Ames dataset.

Development of a project for the thesis “AI in the reduction of cognitive biases (Anchoring Bias) in Brazilian consumption", with the support of Python and Machine Learning.

Code for kaggle single cell competition (got bronze medal)

Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.