This is the development of E-commerce Recomendation system using machine learning website app base

I implemented Machine Learning (Classification) model to give a user recomendation products based on some variables such as how many time they clicked some products, etc

I used the Flask library to deploy the model as a microservice API for our end-to-end website application

I used the Sklearn library to train and process our Machine Learning Model. The fixed model we used in this app was KNN (K-Nearest Neighbors).

THe explanation about the EDA and the model can be senn on EDA.ipynb and Model_Exploration.ipynb

I used https://www.pythonanywhere.com/ as free open source hosting for my website, you can fit the website resolution by pressing ctrl- (zoom out) if the resolution is too big for you or if there is part of the website that you cannot see.

The final dataset that I used after I do some manipulation was FixedDataset.csv which you can find in this repo.

Python 3.9 or above

Install required libraries: pip install -r requirements.txt