Introduction Welcome to the Sales Predictor project! This repository contains code and resources for building a sales prediction model. Sales prediction is a crucial aspect of business planning, helping companies make informed decisions about inventory, marketing, and overall strategy. This README file provides an overview of the project, its contents, and instructions on how to get started.

Project Structure The project is organized into the following directories and files:

data: This directory contains datasets used for training and testing the sales prediction model. Make sure to keep your data organized and labeled appropriately.

notebooks: Jupyter notebooks for data exploration, model development, and evaluation. Use these notebooks to experiment with the data and model building.

src: Source code for the sales prediction model. This directory contains Python scripts and modules for data preprocessing, feature engineering, model training, and prediction.

models: Once the model is trained, it can be saved in this directory for future use.

tests: Unit tests to ensure the functionality of the code.

requirements.txt: A list of Python packages and dependencies required for running the code. Use this file to set up your development environment.

config: Configuration files for model hyperparameters and other settings.

README.md: This document provides an overview of the project and instructions for usage.