MLOps deploying house estimate model

This project deploys a diabetes prediction model on AWS using MLOps principles. It features a Flask-based UI for user interaction and utilizes CI/CD pipelines for automated deployment. By leveraging AWS infrastructure, the project ensures scalability, version control, and monitoring of the deployed model.

This Agentic system is designed to handle complex data analysis tasks by breaking them down into smaller subtasks and delegating them to specialized agents. The system uses a multi-agent architecture to improve performance and scalability.

This project aims to build an end-to-end loan default prediction system for a Non-Banking Financial Institution (NBFI). The system is designed to ingest, clean, process, and predict loan default probabilities while ensuring model deployment, monitoring, and automated CI/CD.

A blog where I siddha-artha(Sankrit for prove meanings) about ML/AI and coding

MLOps with MLFlow for object detection using Tensorflow model.

Documents Participation in the MLOps ZoomCamp by Datatalks Club, showcasing various MLOps practices: Experiment Tracking, Orchestration, Deployment, Monitoring, and Best Practices.

The goal of this project is Build and Tune the hyperparameters of a Sklearn model to predict the target using AWS SageMaker, Deploy the model as a Serverless Inference Endpoint and test it Run Batch Transform on the entire input dataset.

MLOPS end to end project for predicting cancellation of hotel reservations

The real estate app features three modules for predictive pricing, market insights, and personalized recommendations, utilizing machine learning and data analysis. It redefines real estate exploration by empowering users with valuable tools and insights.

Complete Machine learning python flask application for credit Card default Prediction. Features with modular, functional, and object oriented programming.