- Data cleaning and preprocessing using Databricks - Build recommender system using AWS Personalize - Model training and evaluation using AWS Sagemaker - Model Deployment as RestAPI for consumption

- Implementing end-to-end ML pipelines using airflow - Data visualization using Plotly JS - Improving performance of current models - Preprocessing of raw textual data to improve model scoring

- Classification of Images using DNN for document classification - Forecasting of Energy using Time Series Analysis - Classification of frauds in claims - Regression Model for prediction of estimated time of arrival in logistics

- Built a recommender system using item based collaborative filtering - Designed and deployed RestFul API’s for model consumption as a microservice - Built Data pipelines using apache airflow and python - Exploratory data analysis using SQL, BigQuery and pandas

Build scale and automate a full stack application that helps marketing agencies to better manage the ad spending for their clients. - Backend powered by Python Django using relational Postgres database - Frontend using plain html with bootstrap css framework. - Database optimization queries for faster response - API development using DRF

Build and deploy a university internal portal that allows teachers to manage their students, make schedules, allot marks and send emails. - Deployed on custom VM's running linux using Ansible - Email notifications using SMTP - Unit testing using TDD - Management commands for background tasks