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Big-Mart-Sales-Prediction-using-Machine-Learning-

Overview This project aims to predict the sales of products in Big Mart outlets using machine learning techniques. By analyzing historical sales data, the project identifies patterns and trends to forecast future sales, providing valuable insights for inventory and sales strategies.

Dataset The dataset includes attributes like Item Identifier, Item Weight, Item Fat Content, Item Visibility, Item Type, Item MRP, Outlet Identifier, and more, along with the target variable, Item Outlet Sales.

Prerequisites Ensure you have Python 3.x installed. The project relies on libraries such as pandas, numpy, scikit-learn, and matplotlib, among others.

Installation Clone the repository: git clone https://github.com/yourusername/BigMartSalesPrediction.git Install dependencies:

Usage Run the main script to train models and predict sales:

Contributing Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.

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This repository hosts the Big Mart Sales Prediction project, a machine learning initiative designed to forecast product sales across various Big Mart outlets.The analysis includes data preprocessing, exploratory data analysis (EDA), feature engineering, model selection, and evaluation, culminating in insights that can drive business strategies.

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