Slides and other materials from CppCon 2017
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Slides and other materials from CppCon 2017
simplejson is a simple, fast, extensible JSON encoder/decoder for Python
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
A practical hardware and software setup for a compact RL-powered biped robot.
OBD-II serial module for reading engine data
TranslatedTurn PDFs, books and papers into interactive learning webpages | Turn complex materials into learning webpages that are traceable, quizzable, and support note-taking
An information security preparedness tool to do adversarial simulation.
🕵️ Tool to reverse-engineer Protocol Buffers with unknown definition
Scenario for Blender: AI images, video, 3D and PBR materials in the viewport, plus a local MCP server for agents. Blender 5.0+ extension, GPL-3.0-or-later.
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018
Application of asyncio to hardware interfaces. Tutorial and code.
MicroPython Tool - Utility to interact with a MicroPython board over a serial connection.
Python package for stacking (machine learning technique)
FiPy is a Finite Volume PDE solver written in Python
Generative Adversarial Text to Image Synthesis / Please Star -->
We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.
Language Model GRU with Python and Theano
v1.2 - UI tool for manage Espressif ESP32 microcontrollers with embedded MicroPython for MacOS, Windows and Linux: mini IDE, files manager, REPL, real time dashboards (sys/net), advanced features (gpio/mp3/leds/...)
A serialization/deserialization/validation library for strings, mappings and lists.
Android Studio / Eclipse ADT template for material-design-icons resources
Deep Learning Resources and Tutorials using Keras and Lasagne
🎆 A visualization of the CapsNet layers to better understand how it works
The Simplest DCGAN Implementation
TranslatedA basic tutorial for getting started with AI Agents from zero background. It is not just a tutorial but also an Agent that can run locally: read and write files, execute commands, MCP, long-term memory, with a built-in web interface to see every step clearly. Starting from a minimal 100-line loop, each lesson adds one capability, and in the end it breaks down mainstream Agents such as Claude Code and Codex