Hi, I'm Kevin Miller
I am a Senior Python Engineer, Data Professional and Educator with a passion for creating robust, data-driven applications. I enjoy conducting applied research and solving complex problems across various industries. Additionally, I collaborate with industry professionals as a Training Consultant, sharing techniques and insights to help them tackle challenges in Data Analytics and Machine Learning.
CONTACT ME
Software Development | Data Science & Analytics | AI/ML
Machine Learning Projects
PDF Embedding and Query System with LangChain and RAG (AI/ML)
This project demonstrates how to build a system for creating and querying embeddings from PDF documents using LangChain, Chroma, and OpenAI. The system loads PDF files, splits the text into chunks, creates embeddings, and stores them in a vector database. It also provides functionality to query these embeddings for similarity and generate responses.
Technologies Used:
Python, LangChain, Chroma, OpenAI, python-dotenv, shutil, argparse Visit GitHubFamily Face Tracking System (AI/ML)
The Family Face Recognition Tracking System is a Python-based application designed to detect and track faces in real-time using a webcam. This application leverages a foundational face recognition model trained on images of my family members. It identifies known individuals and saves any unknown faces to the filesystem for later review.
Technologies Used:
face_recognition, opencv-python, numpy, matplotlib, seaborn, scikit-learn, threading, argparse Visit GitHub Visit BlogTransfer Learning with PyTorch for classifying bird species (AI/ML)
This project utilizes transfer learning with EfficientNet-B0 for bird species classification. It employs PyTorch’s Dataset and DataLoader for efficient data handling and extends the EfficientNet-B0 model to create a derived model. A training loop was implemented to monitor training and validation losses, and the model's accuracy was assessed on a test set after training.
Technologies Used:
PyTorch, PyTorch Image Model(timm), Pandas, Numpy, Matplotlib Visit GitHub Visit BlogWeb Development Projects
KWIZZ (Python)
Kwizz is an innovative web application designed to enable users to create, host, and participate in competitive quizzes. Kwizz offers a dynamic platform where quiz creators can craft engaging questions and participants can compete in real-time to see who can answer the questions the fastest. Kwizz makes quizzing fun and interactive.
Technologies Used:
HTML, JavaScript, HTMX, Socket.IO, CSS, Bootstrap 5, Python, Flask, Flask-SocketIO, Redis, MariaDB, SendGrid API, Pytest, Docker, gevent, Gunicorn, Docker Compose, Caddy, GitHub, VPS, GHCR, GitHub Actions Screenshots Visit WebsiteMyVideoRama (Go)
MyVideoRama enables users to craft personalized study programs using freely available YouTube videos. Users can create courses, seamlessly add videos to their curriculum, and annotate videos with study notes. This platform empowers learners to structure their learning journey efficiently, harnessing a diverse range of free educational content from YouTube.
Technologies Used:
HTML, JavaScript, HTMX, CSS and Bootstrap 5, Go Standard Library, Redis, MariaDB, SendGrid API, Go Standard, Testing Package, Docker, Docker Compose, Caddy, GitHub, VPS, GHCR, GitHub Actions Screenshots Visit WebsiteNyamUP (Python)
NyamUP is designed to help users manage meals, nutrients, and exercises using data from the Canadian Nutrient File. It provides an intuitive interface for tracking nutritional intake and physical activities, offering a comprehensive solution for maintaining a healthy lifestyle. The application uses modern web tools for a responsive, user-friendly experience.