#javascript #reactjs #nextjs #blogging #publishing #mdx #tailwind_css #demo_blog

https://github.com/timlrx/tailwind-nextjs-starter-blog

#typescript #blog #mdx #nextjs #planetscale #portfolio #prisma #react #tailwindcss #vercel

https://github.com/leerob/leerob.io

#css #cloudflare #docs #mdx

https://github.com/cloudflare/cloudflare-docs

#typescript #markdown #mdx #nextjs #nextra #react #static_site_generator

https://github.com/shuding/nextra

#mdx #css #css_questions #front_end #front_end_development #front_end_interview #front_end_system_design #html #html_questions #interview #interview_preparation #interview_questions #interview_test #javascript #js_questions #web_development

The Front End Interview Handbook is a resource to help you prepare for front-end developer job interviews. It covers various aspects like HTML, CSS, JavaScript, and system design, with different types of questions and formats used by different companies. You can practice with over 200 questions and automated test cases on the GreatFrontEnd platform, which also offers study plans, focus areas, and preparation stages tailored to your needs. This handbook is available in multiple languages and can significantly improve your chances of acing a front-end interview.

https://github.com/yangshun/front-end-interview-handbook

#mdx #chatgpt #deep_learning #generative_ai #language_model #openai #prompt_engineering

Prompt engineering helps you use language models more effectively by designing better prompts. This skill is useful for various tasks like question answering, arithmetic reasoning, and coding. With prompt engineering, you can improve how language models perform and understand their capabilities and limitations. There are resources available, such as guides, courses, and tools, to help you learn and apply prompt engineering techniques. These resources include detailed guides, video lectures, and self-paced courses that can enhance your skills and make you more efficient in using language models.

https://github.com/dair-ai/Prompt-Engineering-Guide

#mdx

This documentation app is built with Next.js and Nextra, making it easy to create and manage documentation. To use it, you need Node.js version 20.11.0 or higher. You can build and run the app using Docker commands, or start a local development server with a few simple steps. The app uses tools like CSpell, Remark, ESLint, Prettier, and Tailwind CSS to ensure high-quality code and documentation. It also has an automated CI/CD pipeline that checks for errors and deploys changes automatically, allowing for live testing and smooth updates. This makes it easier for users to access the latest and most accurate documentation without any manual effort.

https://github.com/inkonchain/docs

#mdx #deep_learning #hacktoberfest #nlp #transformers

The Hugging Face course teaches you how to use Transformers for natural language processing tasks. You'll learn about the Hugging Face ecosystem, including tools like Transformers, Datasets, Tokenizers, and Accelerate, as well as the Hugging Face Hub. This free course helps you understand how to fine-tune models and share your results. It's beneficial because it provides hands-on experience with popular AI libraries and allows you to build and showcase your own projects on the Hugging Face platform.

https://github.com/huggingface/course

#typescript #app_router #content_collections #contentlayer #docs #fumadocs #mdx #next #nextjs #tailwindcss #typescript

The beautiful docs framework with Next.js.

https://github.com/fuma-nama/fumadocs

#mdx #bilateral_teleoperation #force_feedback #genesis #gravity_compensation #humanoid_robot #imitation_learning #machine_learning #moveit2 #mujoco #open_source #openarm #python #reinforcement_learning #robot #robot_arm #robotics #ros2 #teleoperation

OpenArm is a special robot arm that helps with physical AI research. It has 7 degrees of freedom, which means it can move like a human arm. This makes it good for tasks that involve touching or moving things safely around people. The robot is open-source, meaning anyone can build, modify, and use it. This is helpful because it makes advanced robotics available to more people, like researchers and students, without costing too much. A complete system with two arms costs about $6,500, which is much cheaper than similar robots.

https://github.com/enactic/openarm