Event-Sourcing and Domain-Driven Design with F# and EventStore
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AI Roadmap 2026: a beginner's path through Foundations, LLM Engineering, Agents, Evaluation, and Production, with verified free resources and a mini-project per layer
ChatGPT Python Applications integrated with third party libraries and modules
The World's Most Comprehensive, Authoritative, and Structured Open Source Data Source Knowledge Base
- mcp
- data-sources
- ai
- awesome-list
Reference for How to Write an Open Source JavaScript Library - https://egghead.io/series/how-to-write-an-open-source-javascript-library
Vert.x Blueprint Project - A reactive todo-backend implementation using Vert.x and various persistence
- vertx
- restful-api
- asynchronous
- rxjava2
Complete set of all the GoF design patterns implemented in Delphi language
A curated list of all the WWDC Submissions in one place
Una lista de grupos de Slack en español para desarrolladores / A list of awesome Slack groups in Spanish for developers
Koans are small lessons on the path to enlightenment. The aim of the Idris Koans project is to provide an easy learning environment in Idris. Your insight will be derived by encountering failing code and fixing them so that they type check.
Demonstrates how to run load tests with containerised instances of K6, Grafana and InfluxDB
Compilation of games made with flutter and flutter flame
CRAN Task View: WebTechnologies
Translated🐋 Complete guide in Russian: how to install and run DeepSeek locally (V4, R1) on PC, Mac and server — Ollama, llama.cpp, LM Studio, vLLM, Open WebUI, API, RAG, agents, fine-tuning, best tips and tricks
- ai-agents
- deepseek
- deepseek-r1
- deepseek-v4
Ember.js RealWorld Implementation
- realworld
- emberjs
- ember-cli
TranslatedV language study notes
- v
- vlang
Demo app for learning observability with Grafana and performance testing with k6.
A simple note taking app for macOS and iOS which uses Realm and CloudKit for syncing
A drop-in replacement for std::list with 293% faster insertion, 57% faster erasure, 17% faster iteration and 77% faster sorting on average. 20-24% speed increase in use-case testing.
A style guide for Swift.
a curated list of useful threat modeling resources
- threat-modeling
- security
- risk-assessment
Codebase for the Super Rentals official tutorial. Generated by https://github.com/ember-learn/super-rentals-tutorial/. Changes must be made there.
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization
Use this sample when creating a simple pipeline in AWS CodePipeline while following the Simple Pipeline Walkthrough tutorial. http://docs.aws.amazon.com/codepipeline/latest/userguide/getting-started-w.html