aguai1904 Goto Github PK

book-cn

Rust 程序设计语言——Chinese translation of The Rust Programming Language (Book)

carnd-advanced-lane-lines

cplusplusthings

C++那些事

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cv_notes

「3D视觉(三维重建、SLAM、AR/VR) + 传统图像处理 + 计算机视觉(偏AI) 」重要知识点和面试问题。

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

easy_rust

Rust explained using easy English

examples

A repository to host examples and tutorials for Gin.

examples-of-web-crawlers

一些非常有趣的python爬虫例子,对新手比较友好,主要爬取淘宝、天猫、微信、豆瓣、QQ等网站。(Some interesting examples of python crawlers that are friendly to beginners. )

folium

Python Data. Leaflet.js Maps.

gdl_code

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

generative-ai-on-aws

Generative AI on AWS

generative_deep_learning_2nd_edition

The official code repository for the second edition of the O'Reilly book Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play.

gluon-cv

Gluon CV Toolkit

iot-for-beginners

12 Weeks, 24 Lessons, IoT for All!

learnopencv

Learn OpenCV : C++ and Python Examples

machine_learning_tutorials

Code, exercises and tutorials of my personal blog ! 📝

modern-cpp-tutorial

📚 Modern C++ Tutorial: C++11/14/17/20 On the Fly | https://changkun.de/modern-cpp/

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

numpy-ml

Machine learning, in numpy

onnx-simplifier

Simplify your onnx model

onnx-tensorrt

ONNX-TensorRT: TensorRT backend for ONNX

rt-thread

RT-Thread is an open source IoT operating system.

rust

All Algorithms implemented in Rust

rust-raspberrypi-os-tutorials

:books: Learn to write an embedded OS in Rust :crab:

unity3dtraining

【Unity杂货铺】unity大杂烩~

urban_road_filter

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

writing-an-os-in-rust

《使用Rust编写操作系统》

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

yolov5-lite

🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~