While learning some Machine learning, I came up with this idea to better the search on Yelp based on those tons of reviews which get entered everyday on Yelp. This app really helped me learn the ML concepts and understand the complexities of deploying an ML model. Through this post I wanted to share what I have learnt so someone can use this in their path to learn.
Since its really a broad topic and the app includes so many moving components, I will be covering the app and its deployment in two posts. The series will consist of two parts:
1st Post( this one): Overview about the application and about its underlying logic. This will be more about how the app works and the overall architecture of the whole app ecosystem
2nd Post: In 2nd part I will be discussing how I deployed the app on AWS S3 and AWS EKS (Elastic Kubernetes Service) cluster using Codepipeline
Full post for Part 1 can be found here: https://amlanscloud.com/yelpseacrhapp/
A limited demo of the app can be found here:
https://yelp-search-app-demo.netlify.app/
It has a limited dataset included. Only demo zipcode of 61820 can be searched. For e.g: 61820 pasta
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