🎓 I'm a Data Science student at The Hebrew University of Jerusalem and a Data Analyst at the Israel Central Bureau of Statistics (CBS).
🔬 I specialize in machine learning, deep learning, and the application of statistical modeling to real-world data — especially under constraints of scale, latency, and deployment.
🧠 My recent focus is on deep neural network architectures and practical PyTorch implementations, based on my work in the advanced course Introduction to Deep Learning (67822), where I’ve:
- Built and trained convolutional autoencoders (CAEs)
- Explored transfer learning from pretrained encoders to new classifiers
- Studied and implemented RNNs, CNNs, GANs, AEs, diffusion models, and attention mechanisms
- Applied loss landscape analysis, optimization techniques, and theoretical understanding of the functional space neural networks span
📚 Other key repositories include:
- Regression and Statistical Models (52571)
- Statistical Learning and Data Analysis (52525)
- Big Data Mining (52002)
⚙️ Tools & Tech:
- Python, PyTorch, scikit-learn, pandas
- Docker, FastAPI, Redis, SQL, Bash
- NumPy, matplotlib, JupyterLab
🤝 I'm open to collaboration on:
- Deep learning projects using PyTorch or Transformers
- Research or experiments in model optimization, data efficiency, or architectural innovation
- Applied ML pipelines and distributed systems for large-scale analytics
🎸 Fun fact: I love heavy metal and play guitar in my free time.
📫 Reach me: NathanP20@icloud.com
🔗 LinkedIn