class AIMLDeveloper:
def __init__(self):
self.name = "Onur TİLKİ"
self.role = "AI / ML Developer"
self.location = "Ankara, Turkey"
self.core_expertise = [
"End-to-end ML pipelines (data → model → deployment)",
"RAG-based systems and LLM integrations",
"Production-oriented development mindset"
]
def current_focus(self):
return "Designing practical AI systems with real-world constraints"
Binary classification for customer reorder prediction
LightGBM • Docker • Streamlit • Feature Engineering • Class Imbalance Handling
- F1 Score: 0.78 | Recall: 91% | Precision: 69% on 3M+ samples
- 15+ engineered features (user history, product popularity, temporal patterns)
- Complete ML pipeline: EDA → Baseline → Feature Engineering → Production
- Dockerized deployment on Hugging Face Spaces with interactive demo
Intelligent FAQ system for bootcamp participants
LangChain • ChromaDB • Sentence Transformers • MultiQueryRetriever • Streamlit
- Semantic search across 3,232 Q&A pairs with <3 second response time
- MultiQueryRetriever + MMR for improved retrieval accuracy (~95%)
- 40+ keyword mappings with hallucination prevention (<5% error rate)
- Deployed on Streamlit for 150+ concurrent users
Modular regression system with Kaggle validation
scikit-learn • Feature Engineering • RidgeCV • Automated Reporting
- End-to-end pipeline: data ingestion → feature engineering → training → evaluation
- Custom features (TotalSF, Age, BathCount) improving RMSE by 12%
- Automated JSON metrics + feature importance visualization
- Kaggle Score: 0.13049 RMSLE (0.94 R² local validation)
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Machine Learning Engineer • NLP Engineer • LLM Engineer
AI/ML Researcher • Generative AI Developer • MLOps Engineer
📧 Best way to reach me: mehmetonurt@gmail.com
⭐ If you find my projects interesting, feel free to star them!
