Research & Education

Bilby is an AI operating system specifically designed for government entities, offering advanced software for regulation, compliance, and prediction. It leverages custom AI models, knowledge graphs, and multilingual processing to convert complex government activity into hierarchical, clean data and actionable software. The platform has already processed over 75 million artifacts from 130,000 decision-makers across more than 40 countries, creating predictive insights. Bilby aims to improve how the world is governed by providing solutions that offer significant improvements over traditional methods, especially in regions like the Middle East and Asia. Its expert-led innovation, proprietary technology, and global reach make it a comprehensive intelligence solution for government agencies and financial services.

MIRIX is a multi-agent personal assistant that intelligently tracks on-screen activities and answers user questions. It captures real-time visual data and consolidates it into structured memories, transforming raw inputs into a rich knowledge base that adapts to your digital experiences. The system features six specialized memory components (Core, Episodic, Semantic, Procedural, Resource, Knowledge Vault) managed by dedicated agents. It boasts a privacy-first design, storing all long-term data locally with user-controlled settings, and offers advanced search capabilities with PostgreSQL-native BM25 full-text search and vector similarity support. MIRIX also supports multi-modal input, seamlessly processing text, images, voice, and screen captures.

Mallet is an open-source, Java-based package designed for statistical natural language processing and machine learning applications to text. It provides sophisticated tools for document classification, including efficient text-to-feature conversion, various algorithms like Naïve Bayes and Maximum Entropy, and performance evaluation metrics. Beyond classification, Mallet supports sequence tagging for tasks such as named-entity extraction using algorithms like Hidden Markov Models and Conditional Random Fields. Its topic modeling toolkit offers efficient, sampling-based implementations of Latent Dirichlet Allocation and Hierarchical LDA. The package also includes routines for transforming text documents into numerical representations through a flexible system of "pipes" for tokenizing, stopword removal, and count vector conversion. Mallet is ideal for researchers and practitioners working with large text datasets.

Data-Science-Roadmap is an open-source repository designed to guide individuals through a comprehensive self-learning journey in data science. It meticulously outlines a roadmap from foundational concepts to advanced topics, including programming languages like Python and R, statistical analysis, machine learning, and deep learning. The roadmap is structured into beginner, intermediate, and advanced phases, each providing a curated list of free resources such as videos, online articles, and books. It emphasizes practical skills like data cleaning, visualization, and SQL, and offers guidance on preparing a workspace and avoiding common learning pitfalls. This tool is ideal for anyone looking to break into the data science field without financial barriers, offering a structured path and valuable learning materials.

HASH is an open-source, multi-tenant platform designed for creating self-building knowledge graphs and simulations. It integrates data in near real-time and offers powerful interfaces for understanding and utilizing information across various contexts. The platform supports the deployment of intelligent, autonomous agents to grow, check, and maintain the database, integrating and structuring information from both public internet sources and private connected sources. Users, including non-technical individuals, can visually browse and manage entities (data) and types (schemas). HASH aims to serve as a source of truth for critical data, providing a foundation for high-trust, safety-assured decision-making. Future plans include evolving HASH into an all-in-one workspace with AI-generated interfaces, known as "blocks," built on strongly-typed data.

KnowledgeGPT is an AI-powered platform designed for knowledge retrieval and interactive learning. Users can ask questions on any topic and receive beautifully crafted, interactive pages tailored to their curiosity, rather than just a list of links. The platform offers customizable experiences, including interactive courses for language learning, calculators for financial planning, data explorers for product comparisons, visual timelines for historical events, interactive quizzes for general knowledge, step-by-step guides for recipes, and travel guides for destination planning. It aims to transform how users discover and interact with information, making learning and data exploration more engaging and personalized.

nlp_tasks is an open-source repository offering a curated collection of natural language processing tasks and selected references. It aims to provide a clear map of the NLP field, covering a wide array of tasks from Anaphora Resolution to Singing Voice Synthesis. The repository is continuously updated and encourages community collaboration through pull requests. It serves as an excellent starting point for researchers and practitioners looking to delve into specific NLP tasks, with references biased towards recent deep learning accomplishments. Each task entry includes relevant papers, projects, challenges, and datasets, making it a comprehensive resource for academic and practical exploration.

sdupdates is a mega collection of resources and news specifically curated for Stable Diffusion enthusiasts, with a strong focus on AUTOMATIC1111's webui. This GitHub repository serves as a central hub for staying updated on the latest developments, models, and techniques within the Stable Diffusion ecosystem. It includes links to various resources such as new models like Stable Diffusion v2-1-unCLIP and Kandinsky 2.1, ControlNet updates, and text-to-video advancements. The repository also provides practical instructions for updating the webui on both Windows and Linux, and offers contact information for contributions or questions. It's an invaluable resource for anyone looking to deepen their understanding and practical application of Stable Diffusion.

Technical_Book_DL is a comprehensive technical book on deep learning, offering a pedagogical approach to understanding the three most common neural network architectures: Feedforward, Convolutional, and Recurrent. For each architecture, the book meticulously details its fundamental building blocks. It then proceeds to derive the forward pass and the complete update rules for the backpropagation algorithm, providing a thorough understanding for students and AI enthusiasts. The entire document is available as a downloadable PDF, with all figures and LaTeX source files also provided in the repository for compilation. This resource is particularly valuable for those who prefer detailed, indexed formulas over abstract matrix formulations, ensuring a precise grasp of the underlying mechanics.

AIxploria serves as a comprehensive online directory and search engine for artificial intelligence tools, featuring over 9000 listed AI solutions. The platform categorizes tools to facilitate easy discovery, offering a ranking of the best AI tools and a 'Top 10 AI' section that updates in real-time. It aims to bridge the gap between complex AI concepts and practical use cases, providing insights into AI trends and how each AI works through articles. AIxploria also encourages community participation, allowing users to submit new AI tools to keep the directory current and share knowledge. The site is designed for ease of use, offering free access without registration and compatibility across various devices.

Trending-Deep-Learning is a GitHub repository that provides a curated list of the top 100 trending deep learning projects. This resource is updated regularly and sorts repositories based on the number of stars they gained on a specific day. It leverages the GitHub search API with a comprehensive query including terms like 'deep-learning', 'CNN', 'RNN', 'convolutional neural network', and 'recurrent neural network'. Repositories with 40,000 stars or more are excluded to focus on emerging trends. This tool is ideal for researchers, developers, and students looking to stay updated on the latest advancements and popular projects within the deep learning community, offering a quick overview of what's gaining traction.

Top-Deep-Learning is an open-source project that compiles and ranks the top 200 deep learning GitHub repositories. The list is meticulously sorted by the number of stars each repository has received, offering a clear indicator of popularity and community engagement. This resource is invaluable for anyone looking to explore the most influential and actively developed projects within the deep learning domain. It is regularly updated to ensure the information remains current, reflecting the dynamic nature of deep learning research and development. The project's methodology involves querying the GitHub search API using terms like 'deep-learning', 'CNN', 'RNN', 'convolutional neural network', and 'recurrent neural network' to gather comprehensive results.

Nomic is a Python client for Nomic Atlas, a powerful platform designed for interacting with massive unstructured datasets. It enables users to explore, label, search, and share data directly within their web browser. Atlas supports datasets ranging from hundreds to tens of millions of data points, accommodating various modalities including text, image, audio, and video. Key capabilities include generating, storing, and retrieving embeddings for unstructured data, finding insights, and sharing data findings. The platform also offers features like semantic search, topic modeling, data clustering, and deduplication for text, images, video, and audio.

Türkçe Yapay Zeka Kaynakları is a comprehensive, open-source repository dedicated to deep learning and machine learning resources available in Turkish. Supported by the Deep Learning Türkiye community, this platform centralizes a wide array of materials including blog posts, video lectures, scientific articles, code examples, and datasets. It serves as an invaluable hub for individuals seeking to learn or conduct research in AI within the Turkish language. The resource is continuously updated and encourages contributions from the community, ensuring a rich and current collection of information across various AI topics, algorithms, frameworks, and applications.

Notelo is an AI-powered application designed to enhance personal and professional note-taking. It leverages artificial intelligence to automatically organize, summarize, and facilitate the retrieval of user-generated notes. This tool aims to streamline information management and improve productivity for individuals handling large volumes of textual data. By automating the categorization and summarization of notes, Notelo helps users quickly find relevant information and gain insights from their accumulated knowledge. It is particularly useful for those who need to manage extensive textual data, ensuring that valuable information is always accessible and well-organized.

Tradomate offers AI employees capable of performing a wide range of tasks that a human could, operating 24/7 at a fraction of the cost. These AI agents can manage emails, browse the web for information, organize calendars, and conduct research on various topics. The platform is designed to help businesses build, deploy, and scale their AI workforce, providing AI-powered virtual employees that feel human. Tradomate aims to automate daily operations and enhance productivity by offloading repetitive or time-consuming tasks to intelligent AI agents.

yt-channels-DS-AI-ML-CS is a comprehensive, open-source GitHub repository curating over 180 YouTube channels dedicated to Data Science, Data Engineering, Machine Learning, Deep Learning, Artificial Intelligence, Computer Science, programming, and software engineering. This resource is designed to help individuals easily discover educational content and stay updated with the latest trends and tutorials in these rapidly evolving fields. The list is categorized by topic, including Data Science/Analysis, ML/AI/DL, Data Engineering, Statistics/Math, AI research, Programming, Web-dev, Software Engineering, and more, making it simple to navigate and find relevant channels. Users are encouraged to contribute to the list by submitting pull requests, fostering a community-driven approach to knowledge sharing.

Heuris is an AI-powered learning platform designed to make complex subjects accessible through short, engaging 5-minute sessions. It covers a wide range of topics including History, Art, Economics, and Philosophy. The platform leverages AI conversations to guide users through their learning journey, adapting to individual interests and helping to explore new concepts effectively. This approach makes learning efficient and personalized, catering to individuals who enjoy self-directed exploration and quick, digestible content. Heuris aims to provide an interactive and adaptive educational experience for those looking to expand their knowledge in various academic and cultural fields.

The AI Reports serves as a comprehensive AI aggregator, providing a platform where AI tools are ranked and reviewed by users. This allows individuals and businesses to easily identify top-performing AI innovations and steer clear of less effective options. The platform covers a wide array of AI categories, including AI Detection, Art, Voice, Chatbot, Productivity, and more, making it a versatile resource for various needs. By offering user-generated insights, The AI Reports empowers users to make well-informed decisions when selecting AI tools for their specific projects or operational requirements, ensuring they leverage the most suitable and highly-regarded solutions available.

awesome-AI-books is a comprehensive GitHub repository dedicated to providing a curated list of AI-related books and PDFs. It serves as an invaluable resource for students and researchers looking to learn and download materials on artificial intelligence. The repository covers a wide range of topics, including introductory AI theory, mathematics for AI, data mining, machine learning, deep learning, philosophy of AI, quantum AI, and various AI frameworks and libraries. It also features a 'Training ground' section with links to platforms for AI experimentation and research, such as OpenAI Gym and DeepMind Pysc2. All books and PDFs are stored on Yandex.Disk due to GitHub's large file storage limitations, and the repository is intended for learning purposes only.

Awesome-deepseek-coder is a curated list of open-source projects and resources centered around DeepSeek Coder. It provides direct links to official DeepSeek Coder models hosted on Hugging Face, including base and instruct versions across various sizes (1.3B, 5.7B, 6.7B, 33B). Beyond official releases, the repository highlights community-built models that leverage DeepSeek Coder, such as OpenCodeInterpreter-DS and Magicoder-DS. It also features quantized models in AWQ, GGUF, and GPTQ formats, optimized for different deployment scenarios. The list includes integrations with AI coding assistants like Copilot refact and Tabby, showcasing DeepSeek Coder's capabilities in code completion and improvement. Additionally, it points to tools for finetuning data and API examples, making it a comprehensive resource for developers working with DeepSeek Coder.

awesome-explainable-graph-reasoning is an open-source collection of research papers and software dedicated to explainability in graph machine learning. This repository serves as a valuable resource for academics and researchers interested in understanding and implementing explainable AI within graph-based models. It categorizes content into explainable predictions, explainable reasoning, software, and theoretical/survey papers, offering a comprehensive overview of the field. The project is licensed under Apache 2.0, making its resources freely accessible for study and development. It's an excellent starting point for anyone looking to delve into the complexities of interpreting graph neural networks and their applications.

The Artificial-Intelligence-Terminology-Database is a comprehensive, open-source mapping database of English to Chinese technical vocabulary in the artificial intelligence domain. Developed by Jiqizhixin, it aims to assist researchers, translators, and students in accurately understanding and translating AI terminology. The database currently contains over 2400 professional terms, with specialized sections for Machine Learning and AI for Science. It provides indexed terms with English and Chinese translations, common abbreviations, and sources/expansions for conceptual understanding. The project emphasizes accuracy, drawing from authoritative textbooks and literature, and encourages community contributions to continuously improve and expand the terminology.

awesome-ml-model-compression is a comprehensive, open-source curated list of resources dedicated to machine learning model compression and acceleration. This GitHub repository compiles research papers, articles, tutorials, libraries, and tools covering various techniques such as quantization, pruning, distillation, and low-rank approximation. It serves as an invaluable reference for researchers, developers, and students looking to optimize deep neural networks for efficiency, speed, and reduced memory footprint. The repository is actively maintained and welcomes contributions, making it a collaborative effort to advance the field of efficient AI model deployment.