AI Fundamentals
Basic theories, algorithms and mathematical foundations of machine learning
A stable diffusion web interface, developed based on the grado library, provides a friendly browser interface for users to visualize and operate the stable diffusion model conveniently.
An advanced natural language processing model library built for Jax, PyTorch and TensorFlow. It provides a rich set of pre-trained models and tools to help users achieve better results and performance in natural language processing tasks.
A development tool for creating powerful AI applications, it provides APIs for plugins and datasets, as well as an interface for quick engineering and visualization operations. For developers and researchers who want to develop applications, Dify provides convenient tools and interfaces to help them build feature-rich AI applications.
n8n is a secure, flexible workflow automation platform designed for technical teams, combining the power of code with the simplicity of no-code. It offers over 400 integrations, native AI capabilities, and a fair-code license, enabling users to build robust automations while retaining full control over data and deployments. Key features include JavaScript/Python scripting, AI agent workflows with LangChain, self-hosting options, and enterprise-ready functionalities like SSO and advanced permissions. With an active community, 900+ ready-to-use templates, and extensive documentation, n8n supports diverse use cases from simple automations to complex AI-driven workflows. It is source-available, self-hostable, and extensible, making it ideal for both individual developers and large enterprises.
Generative AI for Beginners is a generative artificial intelligence course provided by Microsoft. The course aims to help beginners understand and master the basic concepts and technologies of generative artificial intelligence. Through practical tutorials and examples, learners can gradually explore the world of generative artificial intelligence and lay a solid foundation for in-depth learning in the future.
A reverse engineering project aimed at studying and exploring the working principles of the GPT-4 and GPT-3.5 models. It provides users with an opportunity to understand the internal mechanisms of GPT models and promotes research and improvement of generative pre-trained models.
🤖 An open-source, high-performance chatbot framework that supports voice synthesis, multimodal and scalable function call plugin systems. Users can deploy private ChatGPT/LLM web applications with one click for free, providing powerful chatbot features for projects.
GPT Engineer is highly adaptable, scalable, and enables your agent to understand the desired appearance of your code. Simply specify what you want it to build, and the AI will prompt you for clarifications before constructing it. It generates the entire codebase based on the provided instructions.
A large language model trained by OpenAI, which can be used for chatbots, text generation and question answering systems, etc. Whether you are a beginner or a professional, you can find the corresponding solutions in this project.
An open-source, free search engine known for its excellent performance, ease of use, and simple deployment. It offers instant search experiences, supports multiple languages, and is suitable for projects of various scales. Whether it's a small website or a large enterprise-level application, Meilisearch can provide fast and reliable search functionality.
vLLM is a high-performance, open-source library designed for efficient and scalable large language model (LLM) inference and serving. It features state-of-the-art serving throughput, optimized memory management with **PagedAttention**, and supports advanced techniques like continuous batching, CUDA/HIP graph execution, and various quantization methods (e.g., GPTQ, AWQ, INT4, INT8, FP8). vLLM integrates seamlessly with popular Hugging Face models, offers OpenAI-compatible API servers, and supports distributed inference with tensor and pipeline parallelism. It is highly flexible, supporting a wide range of hardware (NVIDIA, AMD, Intel, TPU, AWS Neuron) and models, including Transformer-based LLMs, Mixture-of-Experts, and multi-modal models. vLLM is community-driven, with contributions from academia and industry, and is backed by sponsors like a16z, Google Cloud, and NVIDIA.
An innovative framework that allows developers to build and develop LLM (large language model) applications using multiple agents. These agents can talk to each other and work together to solve tasks, making the application more intelligent. AutoGen agents are customizable, conversational, and seamlessly integrate artificial intelligence and human involvement to provide broader functionality.
A project called Colossal-AI, which is open-sourced by Chinese people on GitHub, only needs a small amount of modification to enable existing deep learning projects to complete large model training on a single consumer-level graphics card, greatly reducing the cost of project development! In short, with this open-source project, everyone can train AI large models at home! Especially, it has significantly reduced the threshold for fine-tuning, inference and other downstream tasks and application deployment of AI large models.
A free big data analysis database management system (DBMS) designed for handling massive amounts of data. It provides powerful analytical functions that can be used for real-time queries and analysis of large-scale data sets, helping users quickly extract valuable information from massive data.
A tool for building customized low-code machine learning (LLM) workflows using a drag-and-drop UI with LangchainJS. It simplifies the development and deployment of machine learning processes, enabling users to design their own machine learning workflows through drag-and-drop operations, thereby enhancing development efficiency.
Chat-based large language models can interact with third-party systems and dynamically retrieve information.
Microsoft Azure cloud advocates are pleased to offer a 12-week, 24-lesson artificial intelligence course. In this course, you will learn: different approaches to artificial intelligence, including the "good old" symbolic methods of knowledge representation and reasoning (GOFAI). Neural networks and deep learning, which are at the core of modern artificial intelligence. We will use code from two of the most popular frameworks - TensorFlow and PyTorch - to illustrate the concepts behind these important topics. Neural architectures for processing images and text. We will introduce the latest models, but may lack some of the most advanced. Less popular artificial intelligence methods, such as genetic algorithms and multi-agent systems.
A decentralized web AI photo app🌈💎✨. It provides powerful features including photo management, smart categorization, search and sharing. Photoprism uses AI technology to automatically recognize objects, scenes and people in photos, allowing you to easily organize and browse your photo collection.
:🆙 A free and open-source AI image enhancer that uses advanced artificial intelligence algorithms to enlarge and enhance low-resolution images without losing quality. The application is based on the Linux-first philosophy, making it a cross-platform application that supports use on all major desktop operating systems.🎩🪄
Use large models to build WeChat chatbots, based on GPT3.5/GPT4.0/Claude/ERNIE 1.0/Xunfei Xinghuo/LinkAI, support deployment of personal WeChat, official accounts and enterprise WeChat, can process text, voice and pictures, access operating systems and the Internet, support customized exclusive robots based on knowledge bases.
This Python-based toolkit, developed by the Facebook AI Research team, is a sequence-to-sequence modeling toolkit. It offers a comprehensive and robust set of tools and models, suitable for natural language processing tasks such as machine translation and text generation.
An AI coding assistant designed to help developers write code more efficiently. It can provide code suggestions, auto-completion, and error checking, thereby accelerating the coding process. Tabby is an experimental project aimed at exploring how to integrate artificial intelligence into software development workflows to enhance development efficiency.
Netron is a versatile viewer for neural network, deep learning, and machine learning models, supporting a wide range of formats including ONNX, TensorFlow Lite, Core ML, Keras, Caffe, Darknet, PyTorch, and more. It offers experimental support for additional frameworks like TorchScript, OpenVINO, and PaddlePaddle. Available across multiple platforms—macOS, Linux, Windows, browsers, and Python—Netron provides an intuitive interface for visualizing and analyzing model architectures. Users can easily install it via package managers or directly download the application. Sample models are provided for quick exploration, making it a valuable tool for developers and researchers working with diverse machine learning frameworks.
Your AI second brain. A copilot to get answers to your questions, whether they be from your own notes or from the internet. Use powerful, online (e.g gpt4) or private, local (e.g mistral) LLMs. Self-host locally or use our web app. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.
An AI technology roadmap, initiated by the German software company AMAI GmbH, contains relevant knowledge points in the field of AI technology, each of which is accompanied by detailed documents
One-click AI face replacement, only need one face image, no dataset, no training, with built-in sensitive image detection function.
An innovative platform that integrates machine learning into databases through SQL. It treats models as virtual tables (AI-tables), allowing users to directly use SQL queries for time series, regression, and classification predictions without the need for complex data preparation and preprocessing steps. This greatly simplifies the machine learning development process. MindsDB provides developers with a simple and efficient way to accomplish machine learning tasks.
An AI tool that generates short videos with one click. This project is an AI video generation tool based on large model services. You only need to provide a theme or keyword, and it can automatically generate high-definition short videos. It has a simple and easy-to-use web interface, supports batch generation, setting video duration, and horizontal/vertical screen size functions. Shared by @jolahua
A leading stable diffusion model creative engine that enables professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technology. The solution provides an industry-leading web interface as well as support for use via CLI on the terminal. Due to its efficient and flexible features, it can serve as the foundation for a variety of commercial products to meet the needs of different scenarios.
An open-source SDK designed to enable developers to easily integrate AI services such as OpenAI, Azure OpenAI, and hugging Face with traditional programming languages like C# and Python. Through this project, developers can create applications that combine traditional programming and artificial intelligence, expanding the scope of applications and possibilities for innovation.
A set of Go microservice frameworks from Bilibili, including a large number of microservice-related frameworks and tools
A next-generation face changer and image enhancer. It uses advanced image processing technology, allowing users to blend different facial features together to create fun and impressive effects. The potential applications of this project include entertainment, virtual makeup, and artistic creation, providing users with creative tools.
A project that uses artificial intelligence to monitor your security camera. By integrating artificial intelligence technology, frigate can intelligently analyze surveillance footage, providing intelligent monitoring and safety alerts. Whether it's home security, commercial surveillance, or other security scenarios, frigate is a powerful and intelligent monitoring tool.
I have collected a lot of tutorials and example codes related to computer vision, deep learning, and artificial intelligence.
Perplexica is an open-source, AI-powered search engine designed to deliver precise, up-to-date answers by leveraging advanced machine learning techniques like similarity searching and embeddings. It integrates with SearxNG to ensure privacy and real-time information retrieval. Key features include support for local LLMs (e.g., Llama3, Mixtral via Ollama), two search modes (Normal and Copilot), and six focus modes tailored for specific needs like academic research, YouTube, Reddit, and Wolfram Alpha queries. Perplexica offers an API for seamless integration into applications and supports Docker for easy installation. It prioritizes user privacy and provides cited sources for transparency, making it a versatile tool for enhanced web searching.
It can use a crawler to automatically extract and integrate various information from specified URL addresses and generate an output.json data file. By feeding it to ChatGPT, you can quickly customize your own GPT, create a personal knowledge base or intelligent assistant.
The GPT Researcher is an autonomous agent designed to conduct comprehensive online research on a variety of tasks. The agent can generate detailed, factual, and unbiased research reports, offering customized options that focus on relevant resources, outlines, and curricula. Inspired by AutoGPT and recent Plan-and-Solve papers, the GPT Researcher addresses issues of speed and determinacy by employing parallel agent operations (as opposed to synchronous operations), thereby delivering more stable performance and increased speed.
MLC LLM is a universal solution that enables the local deployment of any language model across various hardware backends and native applications, allowing everyone to develop, optimize, and deploy AI models locally on their own devices.
It includes some practical machine learning and Python open source projects and tools. There are more than 900 projects in total, including data visualization, natural language processing, text and image data, web crawling, etc.
A developer-centric information aggregation platform that provides more than 350+ developer information sources and aggregates more than 10,000 technical tags, making it a good channel to get the latest development information.
Chat with your SQL database. This project uses LLM+RAG+database technology to allow users to query SQL databases through natural language and generate SQL answers to your questions.
The Llama Cookbook is the official guide for building applications with Llama Models, offering comprehensive resources for inference, fine-tuning, and end-to-end use cases. It includes tutorials for popular models like Llama 4 Scout and Llama 3.2 Vision, as well as safety-focused tools like Llama Guard. The repository features practical recipes for diverse applications, such as email agents, text-to-SQL, and multimodal inference. Structured into sections for third-party integrations, use cases, and getting started, it also provides FAQs and fine-tuning guidance. The project supports community contributions and adheres to Meta’s licensing and acceptable use policies for Llama models.
The ML YouTube Courses project is dedicated to providing users with the latest machine learning and artificial intelligence courses, all of which can be found on YouTube. By aggregating various educational resources, this project offers learners and practitioners a convenient platform to easily browse, filter, and select course content that suits their learning needs. Whether you are a beginner or a professional, ML YouTube Courses is an ideal choice for discovering quality machine learning educational resources.
Letta is an open-source framework designed for building stateful, long-term memory-enabled LLM applications. It allows developers to create advanced reasoning agents with transparent memory management, supporting various LLM backends like OpenAI, Anthropic, and Ollama. Letta offers a white-box, model-agnostic approach, enabling users to deploy agents via Docker or pip, with PostgreSQL as the recommended database for persistence. The framework includes the Letta Agent Development Environment (ADE), a graphical interface for managing and interacting with agents, and provides REST API and SDKs for integration. Letta is ideal for applications requiring persistent, intelligent agents, such as customer support chatbots, and supports both self-hosted and cloud-based deployments.
A collection of RAG tutorial. This project provides more than 20 advanced RAG technology tutorials, including implementation guides and example codes, which are updated regularly. The content covers various RAG technologies such as retrieval queries, context enhancement, fusion retrieval, hierarchical indexing, context compression, knowledge graph integration, etc.
