Bigmart sales prediction

🛒 BigMart Sales Prediction

🌟 Inspiration

Inspired by how data shapes retail decisions, I built this project to predict BigMart sales using machine learning and analytics.

📘 What I Learned

Data cleaning, feature engineering, and model building

Regression algorithms like Linear Regression, Random Forest, and XGBoost

Model evaluation using

RMSE = \sqrt{\frac{1}{n} \sum (y_i - \hat{y_i})^2}

⚙️ How I Built It

1. Preprocessed and encoded the dataset

2. Trained multiple regression models

3. Tuned hyperparameters for best accuracy

🚧 Challenges

Handling missing/skewed data

Choosing impactful features

Balancing model bias and variance

✅ Outcome

Achieved an score of about 0.90, showing that data-driven insights can power smarter retail forecasting.

Built With

• github
• kaggle
• numpy
• pandas
• python
• regression
• scikit-learn
• xgbooster