GitHub Trends

#other#awesome#awesome_list#c#c_plus_plus#cpp#cpp_library#cppcon#libraries#list#lists#programming_tutorial#resources You can access a vast, well-organized collection of C++ libraries, frameworks, and tools that cover almost every programming need—from standard libraries, GUI, networking, and machine learning to game engines, cryptography, and more. This curated list includes popular and high-quality options like Boost, Qt, OpenCV, and many specialized libraries for tasks such as asynchronous programming, audio processing, and serialization. Using these resources can save you time, improve code quality, and help you build efficient, robust applications by leveraging tested, peer-reviewed components instead of writing everything from scratch. It’s a one-stop reference to boost your C++ development productivity and capabilities. https://github.com/fffaraz/awesome-cpp

#other#public_api You can access a large, well-organized collection of free public APIs for software and web development, covering many categories like animals, anime, finance, weather, health, social media, and more. These APIs provide data and services such as weather forecasts, cryptocurrency prices, job listings, image resources, and text analysis, often with no or simple authentication. Using these APIs can save you time and effort by integrating ready-made data and functions into your projects, helping you build apps faster and with richer features. This list is community-curated and regularly updated, making it a valuable resource for developers. https://github.com/public-api-lists/public-api-lists

#other#communityexchange#cybersecurity#ethical_hacking#hacktoberfest#learn This 90-day cybersecurity study plan helps you build strong skills step-by-step, starting from basics like networking and security principles, then moving to Linux, Python, traffic analysis, Git, ELK stack, cloud platforms, and ethical hacking. It includes daily tasks, videos, tutorials, and practice exercises designed for beginners and professionals alike, even without prior experience. By following this plan, you gain hands-on experience, prepare for certifications like CompTIA Network+ and Security+, and develop confidence in real-world cybersecurity tools and techniques. This structured approach makes learning manageable and effective, helping you start or advance your cybersecurity career. https://github.com/farhanashrafdev/90DaysOfCyberSecurity

#other#clients#mcp The Model Context Protocol (MCP) is an open standard that lets AI models easily and securely connect to different data sources and tools, making it much simpler for developers to build smart apps that can access files, databases, and APIs without custom code for each one[2][3][4]. There are many free and easy-to-use MCP clients—like desktop apps, web apps, and command-line tools—that let you quickly add new AI features and automate tasks, so you can get more done with less effort and technical hassle. This means you can use AI to help with coding, data analysis, and daily work, all while keeping your data safe and your setup flexible[2][3][4]. https://github.com/punkpeye/awesome-mcp-clients

#other This resource is a huge, well-organized collection of computer vision materials including books, courses, papers, software, datasets, tutorials, and tools. It covers everything from beginner to advanced topics like image processing, object detection, 3D vision, deep learning, and more. You can find free and paid courses from top universities, open-source libraries like OpenCV, pre-trained models, and datasets for practice. This helps you learn computer vision efficiently, find the right tools, and stay updated with the latest research and applications, saving you time and effort in your learning or project development. It’s great for students, researchers, and developers. https://github.com/jbhuang0604/awesome-computer-vision

#other#applications#coding#codingchallenges#css#hacktoberfest#html#ideas#javascript#practice You can improve your coding skills by using a collection of app ideas that are organized by difficulty levels: beginner, intermediate, and advanced. Each project comes with clear goals, user stories to guide development, optional bonus features to enhance learning, and helpful resources. This helps you practice daily, experiment with new technologies, and build a portfolio to impress employers or clients. The projects range from simple tools like calculators to complex apps like chat systems or game engines. This structured approach makes learning coding practical, fun, and effective, helping you grow as a developer step-by-step. https://github.com/florinpop17/app-ideas

#other#awesome_list#brasil#ciencia_da_computacao#computer_science#curriculo#cursos#hacktoberfest The MIT License is a simple and permissive software license that lets you freely use, copy, modify, merge, publish, distribute, sublicense, and sell software, as long as you include the original copyright notice and license text in all copies. It does not require you to share your changes or make your code open source. The software is provided "as is," without any warranty, so the authors are not responsible for any problems. This license gives you great freedom and flexibility to use software for any purpose, including commercial, with minimal legal restrictions[1][3][5]. This benefits you by allowing easy and safe use and sharing of software without complex legal barriers. https://github.com/Universidade-Livre/ciencia-da-computacao

#other#artificial_intelligence#artificial_intelligence_projects#awesome#computer_vision#computer_vision_project#data_science#deep_learning#deep_learning_project#machine_learning#machine_learning_projects#nlp#nlp_projects#python You can access a huge, constantly updated list of over 500 artificial intelligence projects with ready-to-use code covering machine learning, deep learning, computer vision, and natural language processing. This collection includes projects for beginners and advanced users, with links to tutorials, datasets, and real-world applications like chatbots, healthcare, and time series forecasting. Using this resource helps you learn AI by doing practical projects, speeding up your coding skills, and building a strong portfolio for jobs or research. It saves you time searching for quality projects and gives you tested, working code to study and modify. https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

#other#beginner#contribution#contributions_welcome#css#frontend#hacktoberfest#html#javascript#open_source#opensource#php#projects#python#react You can find a well-organized collection of coding project ideas divided into three skill levels: beginner, intermediate, and advanced. Each project includes clear goals, user stories, optional bonus features, and helpful resources, making it easier for you to build and extend your projects. This helps you improve coding skills, experiment with new technologies, and create impressive portfolio pieces to attract employers or clients. The list covers various technologies like JavaScript, Python, React, MERN stack, and blockchain, with tutorials and design resources included. You can also contribute ideas and examples to grow the collection and get community support. This resource saves you time and inspires your learning journey. https://github.com/The-Cool-Coders/Project-Ideas-And-Resources

#other#cvrve#internships#jobs#summer_2025#university You can find a detailed, regularly updated list of tech internships for Summer 2026 in the U.S., Canada, and remote options, covering roles in software, quant, data, and more. This list is maintained collaboratively and includes direct application links, company info, and location details. You can also join a Discord community to get instant notifications when new internships open, helping you apply early and connect with peers. The repository encourages contributions, so you can help keep it current. This resource streamlines your internship search, saving time and increasing your chances of landing a great tech internship[5]. https://github.com/vanshb03/Summer2026-Internships

#other#automl#chatgpt#data_analysis#data_science#data_visualization#data_visualizations#deep_learning#gpt#gpt_3#jax#keras#machine_learning#ml#nlp#python#pytorch#scikit_learn#tensorflow#transformer This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently. https://github.com/ml-tooling/best-of-ml-python