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Jopaul07/README.md

Jopaul Nelluvely

Machine Learning Engineer / Applied AI/ML Engineer

Trains and evaluates neural networks in PyTorch, from recurrent models to transformers, and measures results against clear baselines.

🔧 Right now: building an eval-first retrieval system, because "it seems to work" is not a metric

📚 Always: going deeper into neural networks, one backward pass at a time.

🎯 Looking for: Machine Learning Engineer, Applied AI / ML Engineer roles (LLMs, RAG, evals), Bengaluru or hybrid/remote

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  1. seq2seq seq2seq Public

    This series implements sequence-to-sequence (seq2seq) models using PyTorch. Specifically, we'll train models to translate from German to English.

    Jupyter Notebook

  2. nanoGPT nanoGPT Public

    Builds, from scratch in PyTorch, a character-level decoder-only Generatively Pre-trained Transformer (GPT).

    Jupyter Notebook

  3. micrograd micrograd Public

    A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

    Jupyter Notebook

  4. makemore makemore Public

    A progressive series building character-level language models that generate novel names.

    Jupyter Notebook

  5. tinyRNN tinyRNN Public

    Building recurrent neural networks from scratch in PyTorch — a progression from vanilla RNNs to LSTMs to LayerNorm-stabilized LSTMs.

    Jupyter Notebook

  6. openrouter-cli-chat openrouter-cli-chat Public

    Multi-turn CLI chat with OpenRouter models.

    TypeScript