Portfolio
This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes. This portfolio also contains my achievements, skills, and certificates.
Projects
Data Mining - Predictive Maintenance of CNC Machining
In this project I performed Data Mining on Altair AI Studio for three different datasets i,e Tool Forces Prediction model, Tool Wear Detection Time Series model followed by Classification, Machine Usage Condition Data Classification model.
IEEE CIS Fraud Detection Database
The goal of the project was to create and analyze a Transactional Database - IEEE Credit Card fraud detection database. Detection of fraudulent patterns using SQL Analytics. Optimization of Schema Design with partitioning/indexing to handle massive datasets. PL/pgSQL functions for in-database scoring and addressing real-time detection needs.
End to End MLOps Implementation of Web App- Wine Quality Prediction
Developed ML pipeline for Wine Quality Prediction dataset. Worked on the CI/CD Pipeline of the Web App. Deployed the app on AWS S3.
EV Adoption Rates and Geo-Spatial Infrastructure Analysis:
Led a team of 3 to develop an explainable Predicitve ML model for EV sales covering Spatial analysis of State-Level Infrastructure Density Mapping. Feature Engineering and EDA for all the features followed by Statistical Testing. Evaluated all the models based on the metrics. Also Hosted a Visualization Dashboard on PowerBI.
Core Competencies
- Languages: Python, R, SQL, C++
- Methodologies: Machine Learning, Time Series Analysis, Deep Learning, NLP, Statistics, Physics based AI, Explainable AI, Data Structures & Algorithms
- Tools: Docker, PostgreSQL, Git, Flask, MS Excel, Tableau