I'm a Computer Science master’s student at CU Boulder, a UC Berkeley certified Machine Learning & AI professional, and full-stack ready. I’m passionate about applying machine learning, computer vision, and modern development tools to solve real-world problems and create meaningful user experiences.
I transitioned into tech after years of hands-on work as an automotive technician which was an experience that sharpened my ability to work under pressure, think systematically, and solve complex problems. I now bring that same mindset to building and debugging intelligent systems and full-stack applications.
- Languages: Python, JavaScript, SQL, C++
- Frameworks & Libraries: Pandas, Scikit-Learn, TensorFlow, OpenCV, Maptplotlib, Hugging Face, NumPy, Seaborb, PyTorch, React, Express
- Databases: PostgreSQL, SQLite
- Tools: Git, GitHub, Jupyter, VS Code
Predictive Modeling of Car Prices
Explored how different features impact car prices using regression models. Cleaned and processed structured data, ran exploratory analysis, and built predictive models.
Tech: Python, pandas, scikit-learn, seaborn
Classifier Benchmarking for Coupon Acceptance
Compared the performance of multiple machine learning classifiers on a dataset involving consumer coupon acceptance behavior. Focused on accuracy, interpretability, and evaluation metrics.
Tech: Python, pandas, scikit-learn
- 💼 LinkedIn: https://www.linkedin.com/in/david-shamis/
- ✉️ Email: [email protected]
Thanks for visiting my GitHub!