Smartphone Recommender System

Introduction

This project started as the final project from Ironhack's Data Analytics Bootcamp, and currently being further developed.

Scope

The scope of this project is to develop an app that recommends a smartphone with the best cost-effective price, based on a users input.

Basic Structure

Data Source

Data Schema: star schema

Data Storage

ETL pipeline

Machine Learning: Clustering

Deploy: Streamlit

The deploy will be set using Streamlit. In the future, the plan is to use also Heroku for "uploading later to web".

An example of the Streamlit running the deploy can be seen in the following link:
https://drive.google.com/file/d/1f59-gD0I_SQQxPj2nAyJPrZfkbQ3MLUz/view?usp=sharing

Dashboards

This step is one of the final steps. All data processed can be after analysed in dashboards, where prices can be compared between companies, and other statistics displayed.

• Options are: Amazon quicksight,