herokudeployment

Recommendation Engine for E-Grocery store

Table Of Contents

• Demo
• Motivation
• Technical Aspect
• Goal
• Directory tree
• Technologies used
• credits

Demo

link : https://e-groceryrecommendationeng.herokuapp.com/

Motivation

This Project is initiated to help e-grocery stores, owing to the increase in Online sales due to covid. Amazon and netflix recommendation systems are amazing and keeps us engaged while shopping or browsing. This project is a small initiative to understand and reflect all the hardwork behind those.. ' Items you may like..', 'Movies recommended for you..'.!

Technical Aspect

The Project is divided into different sections..

• EDA- cleaing the data and extracting the user-tem matrix
• visualizations - Tableau is used for visualizing the data and draw the insights
• Model building - Lot of traditional algorithms are tested but finally I'm stuck with Lightfm hybrid model owing to it's advantages.
• Flask - Flask app is developed with support of html and css.
• Deployment - The heroku platform is used to deploy the ML model

Goal

The Goal of the project is to engage customer on the app and increase the no. of conversions by giving the appropriate recommendations

Technologies Used

credits

Google.com medium.com