Orchestrated robust end-to-end data science pipelines using Python, handling data ingestion, data validation, data preprocessing, model training, and model deployment using MLFLOW, Streamlit and Amazon EC2
Orchestrated robust end-to-end data science pipelines using Python, handling data ingestion, data validation, data preprocessing, model training, and model deployment using Streamlit to predict Insurance Premium of Customers.
Built a Flask Web Applicaton which operates on Random forest model and predict the Prices of Flight Ticket. Deployed the web app using Docker, Git, Azure Cloud
Predicting Fault Severity on telecommunication network at particular time and location using Machine Learning Techniques
To classify reviews as positive (Rating of 4 or 5) or negative (rating of 1 or 2) based on the text/reviews provided by various users on Amazon using Machine Learning and Natual Language Processing Techniques
Built Tableau Dashboars to Explores various connection which underlie between pollution, health and economic development on a global scale
Orchestrated robust end-to-end data science pipelines using Python, handling data ingestion, data validation, data preprocessing, model training, and model deployment using Streamlit to ensure accurate fraud prediction.