🔎 An HTTP inspector for Android & OkHTTP (like Charles but on device)

Aura Text is a versatile and powerful text editor powered by QScintilla that provides all the necessary tools for developers. It is build using PyQt6 and Python.

24 Lessons, 12 Weeks, Get Started as a Web Developer

Windows Notepad Replacement with Translation, TTS, and much more!

Convert scans of handwritten notes to beautiful, compact PDFs

Declarative statistical visualization library for Python

A Python package for online & offline access to vega datasets

Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML models. It supports text generation, image generation, vision-language models (VLM), auto-speech-recognition (ASR), and text-to-spee…

A collection of standardized JSON descriptors for Large Language Model (LLM) files.

A behavioral analytics library that uses dom mutations and user interactions to generate aggregated insights.

Open-Source Perplexity

A toolbox for integrated information theory.

10 Weeks, 20 Lessons, Data Science for All!

Pyjion - A JIT for Python based upon CoreCLR

Helping developers to use AWS Graviton2, Graviton3, and Graviton4 processors which power the 6th, 7th, and 8th generation of Amazon EC2 instances (C6g[d], M6g[d], R6g[d], T4g, X2gd, C6gn, I4g, Im4g…

Code and website related to the eICU Collaborative Research Database

Open Source Marketplace For Developer Tools

This project is here to enable a fast demo environment on your local environment, Minikube Data Services Kasten K10

A curated list of computer science literature, updated daily.

Probabilistic data structures for processing continuous, unbounded streams.

🗺️ The Next Generation of OpenStreetMap — in Python!

LM Studio CLI

PyTorch tutorials.

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Keras documentation, hosted live at keras.io

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

Tutorials, assignments, and competitions for MIT Deep Learning related courses.