tienthanh1993 Goto Github PK

1m-go-tcp-server

benchmarks for implementation of servers which support 1 million connections

awesome-hacker-search-engines

A curated list of awesome search engines useful during Penetration testing, Vulnerability assessments, Red Team operations, Bug Bounty and more

box2d

Box2D.go - Go port of Box2D - a 2D Physics Engine for Games.

buildingandcraftingandtowerdefensegame

centernet

Object detection, 3D detection, and pose estimation using center point detection:

cloud-game

Web-based Cloud Gaming service for Retro Game

cloudwalker

jumping game cocos2d-x

cocos-google-admob

cocoscreator-multi-resolution-adapter

Cocos Creator 多分辨率适配方案

deep_sort

Simple Online Realtime Tracking with a Deep Association Metric

demoastar

DemoAStar

ebpf-process-anomaly-detection

Process behaviour anomaly detection using eBPF and unsupervised-learning Autoencoders

edgegpt

Reverse engineered API of Microsoft's Bing Chat

every-programmer-should-know

A collection of (mostly) technical things every software developer should know about

falldownball

this source is not owned by me just found on internet.

game_dev_pdfs

Collection of game development related white papers

go-design-patterns

Golang design patterns and use case

go-mind

A neural network library built in Go

golua

Go bindings for Lua C API - in progress

gopher-lua

GopherLua: VM and compiler for Lua in Go

gopherconuk

Repository for GopherCon UK 2018 talk on microservices with Go

gopsutil

psutil for golang

grpc-lb

gRPC service discovery and load balancing library for go

guide

The Uber Go Style Guide.

gym-gomoku

OpenAI Gym Env for game Gomoku(Five-In-a-Row, 五子棋, 五目並べ, omok, Gobang,...)

learningx

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

luar

luar is a Go package for conveniently working with the luago Lua bindings. Arbitrary Go functions can be registered

magika

Detect file content types with deep learning

mini2p_toolbox

The codes, software, models, protocols, and etc. for building and using MINI2P to do the freely-moving recording and analysis. More details can be found in the original paper "Large-scale two-photon calcium imaging in freely moving mice(2021)".

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"