💎 The Design Checklist for Creative Web Designers and Patient Front-End Developers
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💎 The Design Checklist for Creative Web Designers and Patient Front-End Developers
Long list of geospatial tools and resources
Everything that makes working with databases easier
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.
Notes talking about the design and implementation of Apache Spark
The Mobile App Pentest cheat sheet was created to provide concise collection of high value information on specific mobile application penetration testing topics.
:sunglasses: A curated list of awesome MLOps tools
Markdown Cheatsheet for Github Readme.md
Material for my React Fundamentals Workshop
A list of /uses pages detailing developer setups, gear, software and configs.
C++ Syntax, Data Structures, and Algorithms Cheat Sheet
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2026 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Free prompt engineering online course. ChatGPT and Midjourney tutorials are now included!
TranslatedA continuously updated library of source code examples for WeChat Mini Programs and Mini Games. It currently covers more than 120 WeChat Mini Programs or Mini Games.
📃 White paper for Backend developers
:japanese_castle: Better ways to structure iOS apps
TranslatedAll the frontend content you want to know is here
The repository host gives no description.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
Visualizer for pandas data structures
Translated:book: [Translation] scikit-learn (sklearn) Chinese documentation
Translated🔥Best practice project for full technology stack development of microservices based on go-zero (go zero). Develop best practice projects based on the full technology stack of go zero (go zero) microservices.
Translated[Three Years of Interviews, Five Years of Mock Interviews] An interview resource platform for AIGC/LLM/AI Agent algorithm engineers. It covers practical interview and written-test experience and core, cross-cycle knowledge for the AI industry, including AIGC, LLM large models, AI Agents, embodied intelligence, traditional deep learning, computer vision, natural language processing, autonomous driving, machine learning, reinforcement learning, big data mining, world models, the metaverse, AGI, and more.
Bonus materials, exercises, and example projects for our Python tutorials