Research & Education

The Ethical Charter is a valuable resource for anyone interested in the ethical considerations surrounding AI, specifically those outlined by the BigScience organization. This Hugging Face Space allows users to easily access and download the BigScience Ethical Charter. The charter is available in multiple convenient formats, including .txt, .docx, and .html, making it accessible for different uses and preferences. It serves as a foundational document detailing the core values and ethical guidelines that BigScience adheres to, providing transparency and a framework for responsible AI development and research.

Azure-AWS-GCP-DevSecOps-MLOps-Batch-18 is the official GitHub repository for Batch 18 at DevOps Insiders, offering a structured collection of learning materials. This resource includes detailed class notes for quick revision and strengthening core DevOps and Cloud concepts. It also provides assignments for practicing real-world DevOps scenarios and tracking progress. Furthermore, the repository contains practical code samples, such as live demo code, automation scripts, CI/CD pipelines, and configurations for Cloud and Kubernetes, along with DevSecOps and MLOps examples. It serves as a comprehensive hands-on reference for individuals embarking on their DevOps journey, encouraging community contributions to enhance documentation and share optimizations.

Gradio Screen Recorder is a straightforward tool designed for capturing screen activity and saving it as an MP4 video. Hosted on Hugging Face Spaces, it offers a user-friendly interface where users can initiate and terminate screen recordings with dedicated 'Record Screen' and 'Stop Recording' buttons. This tool is particularly useful for quickly creating video demonstrations, tutorials, or capturing specific on-screen actions without the need for complex software installations. It leverages the Gradio framework, making it accessible and easy to integrate for developers working within that ecosystem. Users may need to grant browser permissions for screen and microphone access to utilize its full functionality.

Bootlin's training-materials is an open-source repository offering extensive resources for embedded Linux and kernel development. It provides detailed guides and examples for compiling and understanding various system components, including bootloaders, kernel modules, and device drivers. The materials are designed to be highly practical, with instructions for setting up development environments, compiling code, and performing hands-on labs. It includes formatting guidelines for labs and slides, syntax highlighting with `minted` and `pygments`, and recommendations for diagram creation using Dia. This repository is ideal for individuals and organizations looking to enhance their knowledge and skills in embedded systems programming and Linux kernel development.

Adaptiv Academy is an educational platform designed for continuous learning and skill development. It features a comprehensive array of curated content and interactive lessons, making it suitable for various educational needs. The platform emphasizes real-world applications, ensuring that learners can directly apply their acquired knowledge. Adaptiv Academy also offers personalized learning paths that dynamically adjust to individual user progress, optimizing the learning experience. Furthermore, the platform provides certifications, which can significantly enhance a user's job marketability by validating their newly developed skills.

Curriculum is an open-source content repository developed by Enki, designed to foster a community-driven approach to education. Users can actively participate by editing, commenting on, and contributing to a diverse range of educational materials, primarily focused on programming languages and technical subjects. The platform emphasizes creating a psychologically safe environment for learning, adhering to a contributor covenant code of conduct. It covers topics from blockchain and data analysis to various programming languages like Python, JavaScript, and Java, making it a valuable resource for both learners and educators looking to collaborate on and enhance technical curricula.

Deep-Reinforcement-Learning-Hands-On-Second-Edition is an open-source educational resource published by Packt, designed to help users learn and apply deep reinforcement learning techniques. The GitHub repository provides comprehensive code examples and materials, making it a practical companion for the associated book. It is actively maintained to ensure dependency versions are kept up-to-date, with specific code branches available for major PyTorch versions (e.g., 1.3 and 1.7) to accommodate compatibility needs. The resource includes detailed instructions for setting up a virtual environment using Anaconda, installing PyTorch, and managing other dependencies, making it accessible for hands-on experimentation and learning.

Modern-embedded-programming-course is a comprehensive, free, and open-source companion repository for the "Modern Embedded Systems Programming" video course. This resource is designed to teach users how to program embedded microcontrollers using modern practices, covering fundamental concepts such as binary representations, flow of control, GPIO interfacing, bitwise operations, and object-oriented programming in C. The course emphasizes a deep understanding of what happens inside an embedded microcontroller, focusing on the prevalent ARM Cortex-M architecture. It includes practical, hands-on projects that can be run on various embedded development toolsets like IAR EWARM, KEIL MDK, and TI CCS, and supports hardware like the TivaC LaunchPad and STM32 NUCLEO-C031C6 boards. The course is taught by Miro Samek, an embedded software expert with over 30 years of experience.

Awesome-Autonomous-Driving is a comprehensive GitHub repository maintained by the Autonomous Driving Heart team, serving as a central hub for resources related to the autonomous driving industry. It meticulously organizes surveys, research papers, educational courses, and community discussions, covering the entire technology stack of autonomous driving. The repository provides in-depth learning paths for various sub-domains, including perception (BEV, multimodal, occupancy, radar-vision fusion), localization and mapping (online HD maps, SLAM), multi-sensor calibration, NeRF, visual language models, world models, planning and control, trajectory prediction, and AI model deployment. Additionally, it offers insights into industry-specific technical solutions and facilitates career opportunities through internal referral channels with numerous autonomous driving companies. This platform is designed to foster learning and collaboration among algorithm engineers and researchers.

algorithmic_trading_book is a GitHub repository offering comprehensive resources for individuals interested in algorithmic trading. It includes two distinct books: 'Successful Algorithmic Trading' and 'Advanced Algorithmic Trading'. Each book is provided in PDF format and is accompanied by its corresponding source code, allowing users to study the theoretical concepts and immediately apply them through practical examples. The repository is designed to support learning and implementation of various algorithmic trading strategies, catering to both beginners looking to understand the fundamentals and more experienced traders seeking advanced techniques. All materials are open source, making them freely accessible for educational and development purposes.

David-Silver-Reinforcement-learning is an open-source repository offering comprehensive notes and practical implementations for David Silver's renowned Reinforcement Learning course. It covers a wide range of topics from Week 1 (Introduction to RL) to Week 10 (Case Study: RL in Classic Games), with each week's content including slides and video links. The repository features algorithm implementations using Keras (with TensorFlow backend) and OpenAI's Gym framework, making it a valuable resource for students and researchers. It supports Python, TensorFlow, Keras, Gym, and Numpy, and encourages community contributions for expanding implementations to other frameworks like PyTorch or Caffe.

OccNet-Course offers the first comprehensive course in China on Occupancy Network algorithms, covering everything from BEV (Bird's Eye View) to Occupancy Network principles and engineering practices, including edge-side deployment. This open-source course is designed for autonomous driving enthusiasts and professionals, providing in-depth knowledge on surrounding semantic occupancy perception. It includes detailed documentation, PowerPoint presentations, and source code, making it a valuable resource for both theoretical understanding and practical application. The curriculum covers various aspects such as BEV perception, different Occupancy Network approaches (pure vision, point cloud, multi-modal fusion), important datasets, benchmarks, and deployment strategies for NVIDIA and Horizon J5 chips. The course also features practical coding exercises and a final project to solidify learning.

awesome-cs-cloudnative-blockchain is an extensive open-source repository designed as a growth handbook for individuals interested in computer science, cloud-native technologies, blockchain, web3, and Golang. It offers a curated collection of learning materials, including detailed guides on Go language, Docker, Kubernetes, and various CS fundamentals like operating systems, algorithms, and data structures. The resource also delves into blockchain technology, covering Ethereum, Bitcoin, and Hyperledger Fabric, alongside cryptography and consensus algorithms. It aims to provide a structured learning path for aspiring engineers and those looking to deepen their knowledge in these rapidly evolving fields, with content ranging from beginner to advanced topics and practical project examples.

Robotics-coursework is a GitHub repository maintained by mithi, offering a curated collection of online learning resources for robotics. It serves as a valuable directory for individuals looking to delve into robotics, whether through formal courses, textbooks, or practical projects. The repository categorizes resources into series of courses, single courses, and hands-on projects, making it easy for users to navigate based on their learning preferences. It includes links to platforms like MIT Open Courseware, Coursera, EdX, and Udemy, alongside specific university courses and practical guides for building robots with Arduino or Raspberry Pi. The repository also features sections on useful concepts, tools, and related lists, making it a comprehensive hub for robotics education.

Jello is an innovative platform designed for creating personalized games, offering a unique blend of classic gameplay with user-generated content. Users can easily customize popular games such as Whack-A-Mole and Memory by integrating their own photos and sounds, making each game a truly personal experience. The platform emphasizes ease of use, allowing for unlimited game creation and customization without requiring any coding knowledge. Games can be shared instantly via unique links, and players do not need to download any applications or sign up to play, ensuring a seamless and accessible gaming experience. This makes Jello an ideal tool for individuals looking to create engaging, custom games for personal enjoyment, events, or educational purposes.

Practicing-Federated-Learning is an open-source GitHub repository offering practical code examples for federated learning. It serves as a companion to the book "Practicing Federated Learning," providing hands-on implementations for various chapters. The repository covers topics such as horizontal and vertical federated learning with Python and FATE, personalized recommendations, computer vision, and advanced concepts like attack and defense mechanisms, differential privacy, and homomorphic encryption. It aims to help users understand and apply federated learning to address data silos and user privacy concerns, making it a valuable resource for both academics and industry professionals.

Shadowsocks-Tutorial is a comprehensive, easy-to-follow guide designed for beginners looking to use Shadowsocks to bypass internet restrictions. The resource provides step-by-step instructions for setting up a Shadowsocks server on a VPS, covering everything from purchasing a VPS to installing the Shadowsocks server software. It also includes tutorials for accelerating Shadowsocks with kcptun and configuring client applications across various operating systems like Windows, macOS, Android, and iOS. The guide emphasizes a user-friendly approach, aiming to simplify the process for those who want to access a free internet without needing deep technical understanding. It also addresses common issues and provides troubleshooting tips, making it a practical resource for anyone seeking to set up their own secure internet access.

architecture.of.internet-product is a comprehensive GitHub repository dedicated to cataloging the technical architectures of leading internet companies. It features detailed insights into the system designs of giants such as WeChat, Taobao, Google, Facebook, Amazon, and eBay, alongside Chinese tech firms like Tencent, Alibaba, Baidu, and Meituan-Dianping. The repository is open-source and actively welcomes contributions, making it a dynamic and evolving resource. It's structured with directories for specific companies and thematic categories covering distributed systems, databases, AI/ML, and more, providing a rich learning environment for anyone interested in internet product architecture.

SketchBubble AI is a free AI presentation maker designed to help users create stunning presentations quickly and efficiently. By simply inputting a topic or idea, the AI instantly generates a clear, logical presentation structure with visually appealing slide layouts, relevant images, icons, and charts, all within professionally designed templates. It caters to a wide range of professionals including consultants, entrepreneurs, educators, and business executives, enabling them to build impressive decks without needing design skills. The tool boasts 50x faster presentation generation and has been used to create over 3 million presentations. It offers AI-enhanced designs, instant content creation, a diverse template repository, and supports multiple languages, ensuring seamless compatibility and brand-aligned presentations.

This GitHub repository offers a Chinese translation of the second edition of the influential book "Reinforcement Learning: An Introduction." The project was initiated to provide a valuable resource for Chinese-speaking individuals interested in studying and discussing reinforcement learning concepts. While the project is now in maintenance mode due to the official Chinese translation being published, it still serves as a community-driven effort to make this complex topic more accessible. The repository includes translated chapters and aims to facilitate a deeper understanding of reinforcement learning algorithms and theories.

awesome-reinforcement-learning-zh is a GitHub repository that serves as a curated collection of reinforcement learning resources, primarily in Chinese. It offers a wide array of materials including foundational books like "Reinforcement Learning: An Introduction" by Sutton and Barto, as well as advanced courses from institutions such as UCL, Stanford, UCB, CMU, and National Taiwan University (taught by Hung-yi Lee). The repository is regularly updated with new materials, including recent conference papers and updated course content, making it a valuable hub for anyone looking to delve into reinforcement learning, especially those who prefer resources in Chinese.

Awesome-LongTailed-Learning is an open-source project offering a comprehensive codebase and a curated list of resources focused on deep long-tailed learning. It features a detailed survey that reviews recent advancements in the field, categorizing existing studies into class re-balancing, information augmentation, and module improvement, further broken down into nine sub-categories. The project also provides empirical analyses of various state-of-the-art methods, evaluating their effectiveness in addressing class imbalance issues. Designed to support the research community, it highlights important applications and promising future research directions, making it an invaluable resource for academics and practitioners alike.

Awesome-Mixture-of-Experts-Papers is a comprehensive, curated reading list dedicated to research in Mixture-of-Experts (MoE) models. This open-source GitHub repository provides an organized collection of papers from recent years, categorized by algorithm, system, and application, and further broken down by publication year. It serves as an invaluable resource for researchers, academics, and students looking to explore the cutting-edge advancements in MoE. The project encourages community contributions, allowing users to add missing papers or fix errors, ensuring the list remains current and accurate. It includes papers from major conferences like ICLR, AAAI, ACL, ICML, and NeurIPS, as well as arXiv preprints, offering a broad overview of the field's evolution.

KwaKwa is a mobile learning platform designed to empower creators to build and sell online courses with ease. It simplifies the course creation process by generating lessons, quizzes, pricing structures, and even a landing page based on a description of the creator's knowledge. This tool aims to convert followers into customers by providing a streamlined way to offer digital coaching and educational content. KwaKwa supports the creator economy by offering a mobile business platform for online teaching, making it accessible for individuals to turn their expertise into income without needing extensive technical or instructional design experience. It focuses on helping creators grow their business through mobile courses.