Buscar contenido similar

#engineering#machinelearning#cloud#datascience#python#engineer#aws#mathematics#google Roadmap to Become a Professional Machine Learning Engineer ----- Canal principal:@repo_science Cupones:@freecoupons_reposcience -----

#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

#rust#code_quality#ide#language#language_server#lsp#python#rust#type_check#type_checker#typecheck#typechecker#types#typing Pyrefly is a fast tool for checking Python code. It helps catch mistakes before you run your code, making it easier to write reliable programs. Pyrefly can work with both new and old Python projects, even if they don't have type information. It integrates well with editors like VSCode, providing features like auto-completion and code refactoring. This makes coding faster and more efficient, helping you avoid bugs and making your code easier to understand and maintain. https://github.com/facebook/pyrefly

#python#asr#deeplearning#generative_ai#large_language_models#machine_translation#multimodal#neural_networks#speaker_diariazation#speaker_recognition#speech_synthesis#speech_translation#tts NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3]. https://github.com/NVIDIA/NeMo

#typescript#ai#chatgpt#docsgpt#hacktoberfest#information_retrieval#language_model#llm#machine_learning#natural_language_processing#python#pytorch#rag#react#semantic_search#transformers#web_app DocsGPT is an open-source AI tool that helps you quickly find accurate answers from many types of documents and web sources without errors. It supports formats like PDF, DOCX, images, and integrates with websites, APIs, and chat platforms like Discord and Telegram. You can deploy it privately for security, customize it to fit your brand, and connect it to tools for advanced actions. This means you save time searching for information, get reliable answers with sources, and improve productivity whether you’re a developer, support team, or business user. It’s easy to set up and scales well for many users[2][3][4]. https://github.com/arc53/DocsGPT

https://docs.pipenv.org/ #Pipenv — the officially recommended #Python#packaging tool from Python.org, free (as in freedom). Pipenv is a tool that aims to bring the best of all packaging worlds (#bundler, #composer, #npm, #cargo, #yarn, etc.) to the Python world. #Windows is a first–class citizen, in our world. It automatically creates and manages a #virtualenv for your projects, as well as adds/removes #packages from your #Pipfile as you install/uninstall packages. It also generates the ever–important Pipfile.lock, which is used to produce deterministic builds.

http://www.jaggedverge.com/2017/11/how-a-web-page-request-makes-it-down-to-the-metal/ How a web page request makes it down to the metal by : Janis Posted in : Tutorials, work-in-progess Tags : #NGINX, #Python No Comments The other day I was interested in how many steps occur between sending a #POST or #GET#request from a website to the actual processing that happens on the CPU of the #server. I figured that I knew bits and pieces of the puzzle but I wanted to see the complete path from the highest levels of abstraction all the way to the lowest without missing anything too big in-between. It turns out that in a modern web system there are a lot of steps. I have been really fascinated by this much like the explorer that wants to find a path from one known place to another. If you are interested in better understanding how your computer works you might find walking along this path with your tech stack helpful. Frontend prelude: GET request Browser page #rendering POST request sidenote: #CSRF#token Network stack sidenote: The Internet #TCP sidenote: more comprehensive treatment of network stack Backend Handling web request #WSGI #Django Django URL routing Django views Python implementations #CPython CPython bytecode CPython bytecode execution details Machine Code CPython to machine code Machine code execution Hardware implementation details Microcode Processor #pipeline Silicon implementation of addition Silicon adder unit AND gate Transistor

#python#artificial_intelligence#cloud_ml#computer_systems#courseware#deep_learning#edge_machine_learning#embedded_ml#machine_learning#machine_learning_systems#mobile_ml#textbook#tinyml You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering. https://github.com/harvard-edge/cs249r_book

#cplusplus#apple_silicon#bsd#c_plus_plus#cmake#floss#game#gplv2#json#linux#lua#macos_app#python#strategy#windows Widelands is a free, open-source real-time strategy game like Settlers II, where you lead a small clan to build roads, gather resources like wood and gold, manage four unique tribes, trade, or fight in single-player campaigns and multiplayer. Download it easily for Windows, Mac, or Linux, or compile from source with simple scripts and tools like CMake on various systems. This lets you enjoy deep, replayable empire-building fun at no cost, anytime with friends or AI. https://github.com/widelands/widelands

#python#data_analysis#dingtalk_robot#docker#feishu_robot#hot_news#mail#mcp#mcp_server#news#ntfy#python#telegram_bot#trending_topics#wechat_robot TrendRadar is a lightweight, easy-to-deploy tool that gathers trending topics from 11+ major platforms like Zhihu, Douyin, and Baidu in just 30 seconds. It lets you set custom keywords to filter only news you care about, eliminating information overload. The tool offers three smart notification modes—daily summaries, current rankings, or incremental alerts—and supports multiple channels including WeChat Work, Feishu, DingTalk, Telegram, and email. You can customize how trends are ranked using a personalized algorithm that weighs ranking position, frequency, and hotness. With GitHub Pages for web reports, Docker support, and AI-powered analysis through MCP protocol, TrendRadar transforms scattered platform algorithms into one unified, user-controlled news feed tailored to your interests. https://github.com/sansan0/TrendRadar

#python#agent#agentic#agentic_ai#agents#agents_sdk#ai#ai_agents#aiagentframework#genai#genai_chatbot#llm#llms#multi_agent#multi_agent_systems#multi_agents#multi_agents_collaboration The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects. https://github.com/google/adk-python

#python#cli#cti#cybersecurity#forensics#hacktoberfest#information_gathering#infosec#linux#osint#pentesting#python#python3#reconnaissance#redteam#sherlock#tools Sherlock is a powerful tool that helps you find social media accounts by username across over 400 networks. It's easy to use and works on many operating systems like macOS, Linux, and Windows. You can install it using methods like `pipx` or Docker, and then simply type the username you want to search for. Sherlock will show you where that username is used on different social media platforms. This tool is useful for gathering information quickly and can be run locally or even online through services like Apify. It saves time and effort in finding accounts across many platforms. https://github.com/sherlock-project/sherlock