Sales_forcasting

Live demo to the project result

• Streamlit

Wireframe link for the dashboard

• Wireframing_using_figma

Our Pipe line design

Table of content

• Sales Forcating
  • Overview
  • Requirements
  • Install
  • Data
  • Features
    • Data Exploration
    • Scripts
    • Test

Overview

The aim of this project is to predict the sales six weeks ahead across all the stores of the Rossman Pharmaceutical company using Machine and Deep Learning. The different factors affecting the sales are: promotions, competitions, school-state holiday, seasonality, and locality.

Requirements

Python 3.5 and above, Pip and MYSQL The visualization are made using plotly

Install

git clone https://github.com/Micky373/Sales_forcasting.git
cd Sales_forcating
pip install -r requirements.txt

Data

• The data used in the project is generated automatically by Rossman Pharmaceutical company.
• The data is here

Features

Data Exploration

• Data cleaning is done in the data_cleaning.ipynb
• Data exploration is done in the data_exploration.ipynb
• Data preprocessing and ml modeling is done in the data_preprocessing_and_ml_modeling.ipynb
• Deep learning modeling is done in the deep_learning_modeling.ipynb

Scripts

• All the scripts used by the notebooks are inside the scripts folder.

Test

• Tests for the scripts are inside the tests folder.