- 🎓 Computer Engineering Graduate from Giresun University (GPA: 3.30/4.00)
- 🤖 Passionate Machine Learning / AI Engineer with hands-on experience in Computer Vision, NLP, and MLOps
- 📊 Built projects in image classification, sentiment analysis, and automated ML pipelines
- 🔍 Currently open to full-time opportunities in Machine Learning, Data Science, and AI Engineering
- 📍 Based in Giresun, Turkey — Open to relocation
- ML & AI: TensorFlow, PyTorch, Scikit-learn, CNN, Transfer Learning, BERT
- Data Analysis: NumPy, Pandas, OpenCV, Matplotlib, Seaborn
- MLOps & DevOps: MLflow, Docker, Git, CI/CD, Prometheus, Grafana
- Web & APIs: FastAPI, Streamlit, Flask, REST APIs
- Databases & Cloud: PostgreSQL, Firebase, SQLite, basic AWS/GCP
- Tools & Languages: Python, Jupyter, Google Colab, PyCharm, Anaconda
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🛍️ E-Commerce Customer Segmentation & Sales Prediction
→ RFM + K-Means for segmentation (92% accuracy), Random Forest for sales prediction (R²: 0.99), Streamlit dashboard -
🔄 Automated ML Pipeline with Monitoring
→ End-to-end pipeline with MLflow, Prometheus, Grafana, Docker. Drift detection + Slack alerts. 99% model accuracy -
🎥 Real-Time Image Classification Web App
→ ResNet/EfficientNet with CIFAR-10, served via Flask + Streamlit. Achieved 93.7% accuracy -
🧠 Turkish Sentiment Analysis API
→ BERT-based classifier with FastAPI & Streamlit. Supports real-time and batch analysis (95.2% accuracy) -
🕵️♂️ Copy-Move Forgery Detection
→ Hybrid CNN model using Zernike, BoVW, Color Histograms. GPU accelerated, 94.4% accuracy
☑️ More projects: Real-Time Face & Emotion Recognition, Skin Cancer Detection, Metaheuristic Optimization, and more...
- Neural Networks and Deep Learning – Coursera
- Supervised ML: Regression & Classification – Coursera
- Advanced Learning Algorithms – Coursera
- Unsupervised Learning & RL – Coursera
- Python Programming – Udemy
- +15 other certificates (BTK Akademi, Geleceği Yazanlar)
