A curated list of Multiplayer Game Network Programming Resources
- game-development
- gamedev
- game-programming
- networking
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A curated list of Multiplayer Game Network Programming Resources
A curated list of amazingly awesome Home Assistant resources.
TensorFlow tutorials and best practices.
This repository has examples of broken patterns in ASP.NET Core applications
🔍 A collection of interesting, funny, and depressing search queries to plug into shodan.io 👩💻
:bathtub: Clean Code concepts and tools adapted for .NET
A list of web application security
TranslatedOpen-source manuscript of 《深入理解 AI Infra:量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
Kubernetes application example tutorials
One webpage for every book ever published!
Web Application ASP.NET 9 using Clean Architecture, DDD, CQRS, Event Sourcing and a lot of good practices
HumHub is an Open Source Enterprise Social Network. Easy to install, intuitive to use and extendable with countless freely available modules.
A curated list of Chaos Engineering resources.
SwiftUI sample app using Clean Architecture. Examples of working with SwiftData persistence, networking, dependency injection, unit testing, and more.
Recurrent Neural Network - A curated list of resources dedicated to RNN
Go microservice template for Kubernetes
An Information Security Reference That Doesn't Suck; https://rmusser.net/git/admin-2/Infosec_Reference for non-MS Git hosted version.
A curated list of awesome infosec courses and training resources.
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
The Mobile App Pentest cheat sheet was created to provide concise collection of high value information on specific mobile application penetration testing topics.
This is the new home of the original DDD Sample app (previously hosted at sf.net)..
A curated list of awesome projects related to eBPF.
🎁 A glib-like multi-platform c library
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks