Machine Learning Builder • Learning-in-Public Practitioner • AI Evaluation Enthusiast
I build to learn, and I learn by shipping.
- 🧠 Working across ML fundamentals, LLM evaluation, and practical AI experiments
- 🧪 Interested in ethics, bias, safety, and model behavior analysis
- 🛠️ Building hands-on projects in public: from Naive Bayes / Logistic Regression / PCA to larger evaluation workflows
- 🤝 Open to collaboration on projects where data, experimentation, and impact meet
Many projects optimize only for accuracy. I also care about:
- reliability,
- safety,
- explainability,
- and measurable improvement.
That is why repositories like AETHER-LLM-Evaluation-Platform and EthicsBiasSafety reflect a recurring theme in my work: test model behavior, not just model output.
| Track | Repositories | What it says about me |
|---|---|---|
| Core ML concepts | Naive-Bayes-Theorem, Logistic-Regression, Principle-Component-Analysis--PCA-, BostonHousePricePrediction-using-ML |
I reinforce fundamentals through repeatable experiments |
| LLM learning & evaluation | LLMs-from-scratch, AETHER-LLM-Evaluation-Platform, EthicsBiasSafety |
I care about model internals, evaluation quality, and responsible AI |
| Applied tooling | Data-Analytics-project, Tweet_Scraping, Youtube-video-manager |
I use data workflows to solve practical, real tasks |
Observe → Build → Break → Measure → Explain → Improve
I treat each repository like a mini lab notebook:
- Start with a small, clear baseline
- Add one improvement at a time
- Record what changed and why
- Keep the project understandable for the next learner (including future me)
Python • Pandas • NumPy • scikit-learn • Jupyter Notebook • Matplotlib • Git/GitHub • TypeScript (for app/platform work)
- Deepen ML theory + implementation balance
- Strengthen benchmarking and regression-tracking habits
- Build more end-to-end, reproducible ML projects
- Collaborate more with people building practical AI systems
If you're working on:
- ML experiments,
- LLM evaluation frameworks,
- or responsible AI workflows,
I’d love to connect and build together.
"Progress is my product. Every repo is one more step toward better ML systems."