Rishikesh Fulari

Complete end-to-end MlOps implementation for training, maintaining and monitoring a machine learning model that predicts the price of an old car based on several different relevant factors.
It includes experiment tracking using MlFlow, model orchestration using Prefect and Grafana for monitoring and detecting data drifts. Model has been deployed using Docker and Flask.

Implemented deep learning model to predict if given two questions have same semantic meaning. Utilized Quora question pair dataset and embeddings from pretrained transformers to detect semantic similarity, aimed at finding duplicate questions in forums and Q&A sections employing advanced NLP techniques.

Implemented end-to-end machine learning model to predict if the free-tier user would buy the subscription for e-learning platform ‘365 data science’ using real world platform analytics data.
Data was provided by the Ed-tech platform and the final model was deployed on the Hugging Face Spaces using Streamlit as the front end framework.

Implemented end-to-end Machine Learning pipeline right from data cleaning to model deployment on AWS EC2 instance, demonstrating full stack machine learning skills.
Hospitals in the USA are penalized by the government if the patient is readmitted to the hospital within 30 days. Hospitals however have no means of predicting which patient will be readmitted. This project addresses this problem using machine learning by predicting which patient is likely to get readmitted within 30 days.

Information retrieval system that given a name of brand, retailer or product category/parent category returns the offers that are relevant to the search query.

Fetch Rewards is a mobile app where you can earn free gift cards by scanning and uploading your shopping receipts. You accumulate points for eligible receipts, which can be redeemed for various gift cards. It's a way to get rewards for your everyday shopping. Fetch provides value to their user base through the rich variety of… Show more

Information retrieval system that given a name of brand, retailer or product category/parent category returns the offers that are relevant to the search query.

Fetch Rewards is a mobile app where you can earn free gift cards by scanning and uploading your shopping receipts. You accumulate points for eligible receipts, which can be redeemed for various gift cards. It's a way to get rewards for your everyday shopping. Fetch provides value to their user base through the rich variety of offers that are active in the app. They want their users to be able to easily seek out offers in the app, so that they get the most out of using the app and their partners get the most out of their relationship with Fetch.

Solution Here is a tool that allows users to intelligently search for offers via text input from the user.

How it works ? If a user searches for a brand (ex.Huggies) the tool returns a list of offers that are relevant to that brand, similarly, if user searches for retailer .i.e. Target, it will return relevant offers.

Final deployed app is available at Hugging Face spaces : https://huggingface.co/spaces/rishikesh/search_offers Show less