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YahyaAbuZahra/README.md

“Build models. Ship systems. Keep it reproducible.”


👨‍💻 Yahya Abu Zahra

AI / Machine LearningApplied Data ScienceMLOps (API & Deployment)
Türkiye • Open to Remote / Relocation
Flutter is a secondary skill — I use it mainly to ship ML demos and on-device inference when needed.

EmailLinkedInGitHub


Snapshot

Final-year Computer Engineering student at Bartın University (Türkiye) focused on AI/ML and Applied Data Science.
I design and ship production-minded ML pipelines: data → features → training → evaluation → deployment (API/Docker) → iteration.

I’m most valuable when a team needs:

  • Clean ML pipelines (EDA → features → training → evaluation)
  • Solid baselines & metrics (measurable improvements, not guesses)
  • Deployment-ready models (FastAPI/Flask + Docker)
  • Practical prototypes (sometimes with Flutter as a client) to demonstrate real usage

What I Do

Expertise Working On Focus Areas
Machine Learning & Data Science End-to-end ML pipelines EDA, Feature Engineering, Training, Metrics
NLP (Natural Language Processing) Text models & embeddings TF-IDF, Transformers (BERT), preprocessing, evaluation
Computer Vision (CV) Image-based ML solutions CNNs, OpenCV pipelines, inference optimization
MLOps & Deployment Shipping models to production-like setups REST APIs (FastAPI/Flask), Docker, reproducibility
Flutter (Secondary) ML-powered mobile demos (client layer) UI, API integration, Firebase advanced

Core Strengths

  • ML Engineering: supervised/unsupervised learning, hyperparameter tuning, cross-validation, error analysis
  • NLP: text preprocessing, TF-IDF, embeddings, Transformers (BERT)
  • Computer Vision: CNN-based classification, OpenCV pipelines
  • MLOps / Deployment: REST APIs, Docker, reproducible experiments, version control
  • Data Work: data cleaning, EDA, feature engineering, statistical thinking

🚀 Featured Projects

1) Fake News Detection (NLP) — End-to-End Classification

Tech: Python, scikit-learn, TF-IDF, Logistic Regression / SVM

  • Built a full text classification workflow (preprocess → vectorize → train → validate)

2) AI-Powered Mental Health Screening Prototype (ML + Mobile Demo)

Tech: Python, TensorFlow/TFLite, NLP, CV, Firebase, (Flutter — secondary)

  • Prototype for preliminary screening (no clinical claims)
  • Optimized on-device inference using TensorFlow Lite

3) Travel AI Companion App (AI Integration + Product Thinking)

Tech: OpenAI API, Google Maps API, Firebase, (Flutter — secondary)

  • Conversational trip planning with dynamic itinerary generation

Code & Software Arsenal

Primary (AI/ML & Data)

Deployment & Tools

Secondary (Mobile)

Also


🎓 Education

B.Sc. in Computer Engineering — Bartın University (Türkiye)
Expected Graduation: June 2026


Languages

English: Advanced
Arabic: Native
Turkish: Advanced


Contact


Thanks for Visiting!

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