Pharmaceutical-Sales-Prediction

Table of Contents

• Rossmann Store Sales Prediction
  • Overview
  • Scenario
  • Approach
  • Project Structure
    • data
    • notebooks
    • root folder
  • Installation guide
  • ML Pipeline Design

Overview

In this repository we have a pharmaceutical sales prediction across multiple stores using machine learning and deep learning. This project is part of 10 academy's intensive training.

Scenario

The Rossmann finance team wants to forecast sales in all their stores across several cities six weeks ahead of time.

Approach

This project is divided and implemented by the following phases

1. Exploration of customer purchasing behavior
2. Prediction of store sales
   1. Machine learning approach
   2. Deep Learning approach
3. Serving predictions on a web interface

Project Structure

The repository has a number of files including python scripts, jupyter notebooks, pdfs and text files. Here is their structure with a brief explanation.

data:

• the folder where the dataset files are stored

notebooks:

• the folder where jupyter notebooks reside

root folder:

• .gitignore: a text file listing files and folders to be ignored
• README.md: Markdown text with a brief explanation of the project and the repository structure.

Installation guide

git clone https://github.com/DiyeMark/Pharmaceutical-Sales-Prediction
cd Pharmaceutical-Sales-Prediction
pip install -r requirements.txt

ML Pipeline Design