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+# Rossmann Store Sales Forecasting
+
+## Project Overview
+This project aims to forecast sales for Rossmann Pharmaceuticals across their stores, six weeks in advance. It leverages machine learning and deep learning techniques to predict daily sales, taking into account factors such as promotions, competition, holidays, seasonality, and locality.
+
+## Business Context
+Rossmann's finance team requires accurate sales forecasts to facilitate better resource planning and financial decision-making. This project provides an end-to-end solution that delivers these predictions to finance team analysts.
+
+### Main Objectives
+
+1. Exploration of customer purchasing behavior
+2. Prediction of store sales
+
+## Folder Structure
+
+- `notebooks/` : Jupyter notebooks for all the analysis.
+- `scripts/`   : Python scripts for the notebook files .
+
+
+## Notebooks Folder/ 
+
+```
+    `preprocessing.ipynb`      : contains a scripts for or data cleaning and processing 
+    `ml_preprocess.ipynb`      : contains a script for data preparation  to train a model
+    `ml_modelling.ipynb`       : contains a script for for Regression model training 
+    `dl_modelling.ipynb`       : contains a script for LSTM model training 
+```
+
+
+## Setup Instructions
+1. Clone the repository.
+2. Set up the virtual environment.
+3. Install dependencies using `pip install -r requirements.txt`