Data Scrapping

Find the data needed to train the model.

Data Cleaning

Clean the data by removing outliers and normalising the data for a format acceptable by the model.

Data Wrangling

Find interesting patterns or relationship within the data

Modelling

Building a machine learning model for the specific use case

Hosting and API

Build an APi that will interface with the model. Optionally host the project to the clients server

Frontend

Build a minimal webapp that will interact with the model