Notebooks for Kaggle competition
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Updated
Jan 25, 2025 - Jupyter Notebook
Notebooks for Kaggle competition
Detecting brain age based on MRI scans data.
Linking Writing Processes to Writing Quality
Dynamically adjust cost of the rides in response to changing factors
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.
Leveraging Machine Learning 🚀 to predict Math Scores 📈 based on key features, Enables data-driven insights for better academic support and improvement strategies! 🚀
Accident damage prediction using catboost regressor
Math Score Predictor
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, machine learning model & deployment using Flask & Render.
Predicting house prices using advanced regression algorithms
Estimating abalone rings (age) based on their physical characteristics, such as gender, length, height, diameter, weight, etc.
House Price Prediction
Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.
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
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.
End-to-end House Price Prediction system using Machine Learning, featuring data preprocessing, model training, and deployment via Streamlit UI and FastAPI REST API.
Code for kaggle single cell competition (got bronze medal)
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