🔒 A compiled checklist of 300+ tips for protecting digital security and privacy in 2026
- privacy
- security
- censorship
- cybersecurity
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🔒 A compiled checklist of 300+ tips for protecting digital security and privacy in 2026
🚀 A curated collection of AI engineering resources, roadmaps, tools, and projects covering LLMs, RAG, AI Agents, MCP, fine-tuning, evaluations, and production AI systems.
TranslatedA Python web scraping tutorial series, learning Python web scraping from 0 to 1, including browser packet capture and mobile APP packet capture with tools such as fiddler and mitmproxy, the use of the various modules involved in web scraping, such as requests, beautifulSoup, selenium, appium, scrapy, etc., as well as IP proxies, CAPTCHA recognition, using Mysql and MongoDB databases with Python, multi-threaded and multi-process scraping, reverse engineering and cracking of CSS scraping encryption, JS scraping reverse engineering, distributed scraping, practical scraping project examples, etc.
List of ngrok, Cloudflare Tunnel, Tailscale, and ZeroTier alternatives and other tunneling software and services. Focus on self-hosting.
TranslatedProgrammer Yupi's (程序员鱼皮) complete AI resource collection + zero-basics Vibe Coding tutorial. Shares step-by-step OpenClaw tutorials, ways to use large models (DeepSeek / GPT / Gemini / Claude / GLM), the latest AI news, a complete collection of Prompts, an AI knowledge encyclopedia (Agent Skills / RAG / MCP / A2A), AI programming tutorials (Harness Engineering), guides to using AI tools (Cursor / Claude Code / TRAE / Codex / Copilot), AI development framework tutorials (Spring AI / LangChain), and a guide to monetizing AI products, helping you quickly master AI technology and stay at the forefront of the times. This project is the open-source documentation aiguide, which has been upgraded to the Yupi AI Navigation website (鱼皮 AI 导航网站)
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
TranslatedThe pytorch handbook is an open-source book that aims to help friends who want to use PyTorch for deep learning development and research get started quickly. All of the PyTorch tutorials it contains have been tested to ensure they run successfully.
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
A collection of awesome .NET libraries, tools, frameworks and software
:honeybee: A collection of awesome .NET core libraries, tools, frameworks and software
This repository contains a 90-day cybersecurity study plan, along with resources and materials for learning various cybersecurity concepts and technologies. The plan is organized into daily tasks, covering topics such as Network+, Security+, Linux, Python, Traffic Analysis, Git, ELK, AWS, Azure, and Hacking. The repository also includes a `LEARN.md
🎮 A step-by-step guide to implementing SSAO, depth of field, lighting, normal mapping, and more for your 3D game.
Translated🚀 Free subscription address, 🚀 Free node, 🚀 Updated every 6 hours, shared node, high-quality node availability, completely free. Free clash subscription address, free ss/v2ray/trojan node. Also: free firewall circumvention, free "scientific internet access", free ladder, Google store, firewall-circumvention ladder.
Machine Learning Engineering Open Book
A curated list of awesome applications, softwares, tools and shiny things for macOS.
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
A quick example of how one can "synchronize" a 3d scene across multiple windows using three.js and localStorage
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
Everything you need to prepare for your technical interview
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
machine learning and deep learning tutorials, articles and other resources
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
💿 Free software that works great, and also happens to be open-source Python.