- Projects in machine learning, deep learning, and data science
- Experiments in programming and modeling
- Studies and notes on AI concepts
Here are some of my projects:
🔹 Enhancing GANs with Discriminator Rejection Sampling
Worked on improving GANs by implementing Discriminator Rejection Sampling (DRS) and adaptive truncation. This technique enhanced sample quality and diversity in generated images.
🔹 Fraud Detection using Machine Learning
Developed a fraud detection model using Gradient Boosting and Random Forest to analyze transaction data. Achieved 1st place in the ENS Challenge Data competition with an optimized Precision-Recall AUC score.
🔹 Real Estate Price Prediction
Built a predictive model for estimating real estate prices based on structured data. Implemented advanced feature engineering and XGBoost optimization.
🔹 Lymph Node Metastasis Detection – ENS Challenge Data (May 2025)
Participating in the ENS Challenge Data, working on automated detection of lymph node metastases in breast cancer patients using histological images. Exploring machine learning and deep learning techniques to improve classification performance and assist in cancer diagnosis.