Machine_Learning_Projects

This repository contains my machine learning projects, ranging from beginner-level implementations to more advanced real-world applications. The projects cover data preprocessing, feature engineering, model building, evaluation, and practical problem-solving using Python libraries such as Pandas, NumPy, Scikit-learn, and NLTK

Big Mart Sales Prediction Model:

This repository contains the code and analysis for a data science project focused on predicting 'Outlet_Item_Sales'. It includes data preprocessing, exploratory data analysis, machine learning model development XGBoost, hyperparameter tuning, and model evaluation. The goal is to build a robust predictive model and understand key factors influencing Outlet_Item_Sales

Model Type R2 Score (Training) R2 Score (Testing)

Plain XGBoost train -> 0.864 test -> 0.534
GridSearchCV Tuned train -> 0.628 test -> 0.605
RandomizedSearchCV Tuned train -> 0.633 test ->0.595

datasets

https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_movies.csv https://www.kaggle.com/ninzaami/loan-predication https://www.kaggle.com/datasets/kazanova/sentiment140 https://www.kaggle.com/datasets/yasserh/wine-quality-dataset