Paper implementations from scratch and machine learning tutorials

AI on the way. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.

Below are some simple methods for exiting vim.

Natural Intelligence is still a pretty good idea.

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Official PyTorch implementation of StyleGAN3

Free Book about Deep-Learning approaches for Chess (like AlphaZero, Leela Chess Zero and Stockfish NNUE)

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

PyTorch Framework for Developing Memory Efficient Deep Invertible Networks

Pytorch library for fast transformer implementations

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

Synthetic data generation for tabular data

Connect to Google Colab using SSH

Run VSCode (codeserver) on Google Colab or Kaggle Notebooks

torch-optimizer -- collection of optimizers for Pytorch

Algorithmically generated triangle art

A Tailwind CSS component that shows the currently active screen (responsive breakpoint).

Brotli compression format

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

Configuration file support for Click applications

Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

A terrible way of testing terminal applications

All Algorithms implemented in Python

Automatic SQL injection and database takeover tool

Web path scanner

Metasploit Framework

Python implementation of GLN in different frameworks

Official implementation of "Implicit Neural Representations with Periodic Activation Functions"

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Fast Differentiable Sorting and Ranking