Capstone

Introduction

This is the final project of the AltSchool Data Science Track.

Project Structure

.
├── README.md
├── client
└── src
    ├── data
    ├── models
    ├── notebooks
    ├── server.py
    └── utils

Goals

• Data Preprocessing and EDA (finding patterns, trends)
• Data cleaning (Removing items with zero sales from the Sales Dataset)
• Modelling
• User Interface
• Flask server

Setup

• Clone the repo
• Large files (such as models and train.csv) are stored in Git LFS. Install Git LFS and run git lfs pull to download them.

Server Setup

• Install Python 3
• Create a virtual environment using python3 -m venv venv
• If you're on Linux or MacOs, activate the virtual environment using source venv/bin/activate
• If you're on Windows, activate the virtual environment using venv\Scripts\activate.bat
• Install requirements using pip install -r requirements.txt

Client Setup

• Install Node.js
• Install packages using npm install

Running locally

• If you're on Linux or MacOS, start the server using npm run dev:win-server
• If youre on Windows, use npm run dev:win-server to start the server
• In another terminal run the client using npm run dev:client

Client will be available at http://localhost:3000 Server will be available at http://localhost:5001