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SnoopyCraze/README.md

Hi, I'm Zeran (Or you can call me Snoopy)

I'm a machine learning engineer who likes to build AI/ML models all the way to production! Most of my time goes to Polycreek, a child-safety nonprofit I founded and lead, where I built and run a grooming-detection classifier that serves partner platforms in production.

What I work on

  • Fine-tuning transformer models (SFT, LoRA/QLoRA) and shipping them: quantized inference, scale-to-zero GPU serving, eval harnesses, and release gates that actually block bad models.
  • At Polycreek the production classifier is a ModernBERT backbone with seven classification heads, running at 0.98 recall and a 0.011 false-positive rate on roughly 10k requests a day.
  • Contract work as a SME on model architecture, evaluation and post-training data pipelines for frontier AI labs.

Research I published an empirical study on why overparameterized networks generalize: Implicit Regularization and Generalization in Overparameterized Neural Networks (arXiv:2604.07603). It covers SGD batch-size effects, flat vs. sharp minima via Hessian analysis, double descent, the neural tangent kernel, and the Lottery Ticket Hypothesis on CIFAR-10 and MNIST. Code and figures are here: overparameterized-generalization.

I have a few other ongoing research projects in the fields of RSI, Emergence and Agentic Failure Prediction which are soon to be published in late 2026 to early 2027

A few things I've built for fun

Toolbox: Python, Rust, PyTorch, HF Transformers, FAISS/pgvector, Docker, AWS, Terraform and more that I don't think anyone would care to read!

Elsewhere: polycreek.org · LinkedIn
Always open to conversations with likeminded engineers!

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    Datapack is a universal TypeScript data toolkit. Define a schema once and reuse it everywhere to validate, transform, serialize, fetch, and store data through one cohesive API. It unifies jobs norm…

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  2. overparameterized-generalization overparameterized-generalization Public

    Why overparameterized neural nets generalize: controlled experiments on implicit regularization, flat minima, double descent, NTK, and the Lottery Ticket Hypothesis (MNIST/CIFAR-10, PyTorch). Code …

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