Notebooks for Kaggle competition

Detecting brain age based on MRI scans data.

Leveraging Machine Learning 🚀 to predict Math Scores 📈 based on key features, Enables data-driven insights for better academic support and improvement strategies! 🚀

Linking Writing Processes to Writing Quality

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.

Accident damage prediction using catboost regressor

Dynamically adjust cost of the rides in response to changing factors

Math Score Predictor

House Price Prediction

Predicting house prices using advanced regression algorithms

A machine learning project to predict house prices based on key features for informed real estate decisions.

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

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.

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

A light-weight Kaggle challenge to predict crabs' age

Student Performance Predictor is an end-to-end machine learning project that implements a complete predictive modeling pipeline. It analyzes the impact of demographic, socioeconomic, and academic factors on student mathematics performance, performing data preprocessing, feature engineering, regression modeling (Linear, Ridge, Lasso, Random Forest,

Code for kaggle single cell competition (got bronze medal)