Data Scientist, Engineer, AI, Educator
This project implements an automated MLOps pipeline for deploying a machine learning model, focusing on operational efficiency and security. It integrates Jenkins for CI/CD, Docker for containerization, and AWS ECS for scalable deployment, ensuring a repeatable and reliable workflow. Project Overview The pipeline automates the deployment of a Flask-based ML application, emphasizing Continuous Integration and …
This project demonstrates the deployment of a machine learning model using Docker and Kubernetes on Google Cloud Platform (GCP), highlighting skills in MLOps, containerization, and cloud infrastructure management. The process integrates a pre-trained PyCaret model into a Flask application, containerized with Docker, and orchestrated with Kubernetes for scalability and reliability. Project Overview Key Steps Outcomes …
This project is a hands-on implementation of a real-time algorithmic trading system that processes market data and news sentiment to make automated trading decisions. It integrates Apache Flink for stream processing, Redpanda for data streaming, and the Alpaca API for market data and trade execution, with sentiment analysis driving the strategy. Technologies Used How It …
This project is a real-time anomaly detection system for stock trading data, built with Redpanda and Quix. It processes streaming trade data and flags unusual patterns using both rule-based and machine learning techniques. Purpose The goal is to detect anomalies—like sudden price jumps or high-volume trades—as they happen, using a lightweight, practical setup. Technologies Used …
This project demonstrates the creation of an employee churn prediction pipeline using Google BigQuery, PyCaret, and Looker Studio. The goal is to predict which employees might leave based on historical data and offer insights to boost retention. Technologies Used Key Features Link: Read the full article on Medium Code: https://github.com/shj37/Employee-Churn-Prediction-with-Looker-Studio-BigQuery-and-PyCaret
This project combines Retrieval-Augmented Generation (RAG) with AWS for scalability, GitHub CI/CD for automation, and Docker for deployment reliability. It’s a practical dive into AI and DevOps that’s transforming education. Check out the full story on Medium: Read the article from developers’ perspectives, Read the article from educators’ perspectives. Github: https://github.com/shj37/medical_aws_CICD
Summary Skills: Fine Tuning · Large Language Models (LLM) · Natural Language Processing (NLP) · TPU · GPU · Artificial Intelligence (AI) · LoRA · QLoRA · FinTech · financial risk compliance · Chatbot Development · Keras · PyTorch · Project Management · Gemma-2b · Gemma-7b · Data Cleaning · Synthetic Data Generation Highlights Project …
Role: Student AI Researcher at Skinopathy Skills: Artificial Intelligence (AI) · speech-to-text · Fine Tuning · QLoRA · Natural Language Processing (NLP) · Text-to-Speech Synthesis · Data Processing · Data Cleaning · OpenAI Whisper · Audio Recognition · Project Management
I conducted some preliminary tests to assess the efficacy of employing GPT-4 for analyzing reference documents and generating answers for tasks assigned in the first semester of my graduate certificate program. It’s worth noting that this project was carried out post-completion of those courses, and therefore, was not utilized for the assignments associated with those …
In the realm of online shopping and entertainment, we often encounter personalized recommendations like “You may also like this item” or “Recommended movies based on your preferences.” These suggestions stem from association rule mining algorithms, specifically market basket analysis. This method uncovers item relationships from historical data, shedding light on customer behavior and preferences. Recently, …