Developed an end-to-end ML system on Azure to predict loan defaults, leveraging advanced data preprocessing, feature engineering, and machine learning models to optimize accuracy. This project includes a comprehensive suite of tools and techniques for robust financial risk assessment, deployed to enhance decision-making for high-risk exposures.
[AAAI 2022] Detecting Human-Object Interactions with Object-Guided Cross-Modal Calibrated Semantics.
End-to-end PSF extraction for 3D microscopy
Deep Negative Volume Segmentation - automated 3D CT segmentation of body joints for dentistry
Supported Models: MobileNet [V1, V2, V3_Small, V3_Large] (Both 1D and 2D versions with DEMO, for Classification and Regression)
A Fully Automatic Method for Predicting Contact Maps of RNAs by Evolutionary Coupling Analysis
End-to-End ETL Pipeline for Film Data Crawling from Ohitv
CI/CD pipeline to deploy Node.js app to AWS using Terraform, Ansible, and GitHub Actions. Fully automated deployment on every push to main branch
End-to-end data engineering pipeline with real-time streaming, cloud processing, and analytics. Built with Apache Kafka, Spark, AWS Glue, and Snowflake using Apache Iceberg tables.
Analyzed a multicategory e-commerce store using big data techniques on a Kaggle dataset with the help of AWS EC2, AWS S3, PySpark, AWS Glue ETL, AWS Athena, AWS CloudFormation, AWS Lambda and Power BI!
End-to-end Fraud Detection MLOps pipeline integrating MLflow, FastAPI, Streamlit, Docker, Kubernetes, Prometheus, and Grafana for real-time fraud prediction, experiment tracking, and monitoring.
The Ultimate DevOps Portfolio: Real-world, end-to-end projects integrating industry-leading tools to mirror enterprise-level workflows
A cloud-based tool for sentiment analysis in reviews about restaurants on TripAdvisor
Successfully established a machine learning model which can accurately predict the expected life duration of a human being based on several demographic features such as alcohol consumption per capita, average BMI of entire population, etc.
Full-stack MLOps pipeline for predicting colorectal cancer patient survival using Gradient Boosting, Kubeflow Pipelines, MLflow, and Flask. Designed for hospitals, researchers, and real-world healthcare applications.
This project is a NLP problem that will be the foundation of an English program used by the company Easy Sailing Language Training.
End-to-End Data Pipeline for NYC Green Taxi trip data using Azure Data Factory, Data Lake, and Databricks following the Medallion architecture
Detect U.S. housing market bubbles using macroeconomic signals. Forecast HPI, score speculative risk, and visualize insights using a fully modular, cloud-native GCP pipeline.
This project is an end-to-end MLOps pipeline for a network security system that detects phishing and malicious activities using machine learning. It automates data ingestion, preprocessing, model training, and deployment while leveraging AWS S3 for model storage and GitHub Actions for CI/CD. The system includes realtime monitoring & a web interface
Spell Corrector functionality for medical domain in Scala which consists modules to build a medical word corpus and correct misspelled words.
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