An OS which is all about learning!
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Updated
Mar 26, 2026 - Rust
An OS which is all about learning!
A from-scratch implementation of a feedforward neural network in C# (.NET 8) without using any machine learning frameworks.
A convolutional neural network (CNN) built from scratch using only NumPy to classify handwritten digits from the MNIST dataset.
Educational, from-scratch implementation of a LLaMA-style LLM using PyTorch to explore Transformer architecture fundamentals.
Implementation of KNN and Gaussian Naive-Bayes algorithms to classify phishing URLs. Built from scratch and compared with scikit-learn versions.
This project demonstrates how to build and train a feedforward neural network from scratch using only NumPy, without any high-level deep learning libraries like TensorFlow or PyTorch. The model is trained on the MNIST digit classification dataset and achieves competitive accuracy.
Minimal http server written from scratch in C language
"Learn Linear Regression: A Python implementation from scratch with dataset generation and visualization" as it's both informative and engaging.
Manual implementation of backpropagation on a custom computational graph with gradient checking. Benchmarks Vanilla SGD, Momentum, and Adam optimizers from first principles using NumPy.
From-scratch implementation of binary Logistic Regression using NumPy, with vectorized cost computation, gradient calculation, and batch gradient descent optimization.
LSTM implemented from scratch and with PyTorch's nn.LSTM, trained using PyTorch Lightning on a toy stock prediction task. Educational and beginner-friendly.
Minimal GPT implementation from scratch using PyTorch — trains a character-level transformer on the Tiny Shakespeare dataset to demonstrate core LLM concepts.
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