Research & Education

Search Your Face Online is a reverse face search tool designed to help individuals monitor their digital footprint. By uploading a face image or providing a name, email, or phone number, the tool scans various public and private online sources. It then identifies potential matching profiles, linked accounts, and contact information, allowing users to understand where their image or personal data might appear online. This can be particularly useful for managing online privacy, identifying unauthorized use of personal images, or simply gaining insight into one's overall online presence across different platforms.

pyprobml is an open-source Python code repository designed to accompany Kevin Murphy's "Probabilistic Machine Learning: An Introduction" and "Probabilistic Machine Learning: Advanced Topics" books. It provides Python 3 code to reproduce all the figures presented in these textbooks, utilizing widely-used libraries such as NumPy, SciPy, Matplotlib, and scikit-learn. Additionally, the codebase incorporates modern machine learning frameworks like JAX, TensorFlow 2, and PyTorch for more advanced topics. The project is currently in maintenance mode and offers various ways to run the notebooks, including Google Colab for cloud-based execution with free GPU/TPU access, or locally after installing dependencies. It also provides utility code via probml-utils and guidance for contributions.

TAP is transforming youth employment across Palestine, Lebanon, and Jordan by blending AI innovation with the power of networks. This platform offers AI-driven tools, personalized coaching, and mentor support to help job seekers land meaningful roles. It connects talent, employers, and global allies to build sustainable careers and stronger futures for MENA youth. TAP's approach includes carefully selected and vetted talent, mentorship, and coaching, creating a pool of skilled, job-ready professionals. The platform also facilitates partnerships with NGOs, international organizations, and employers to enhance employability across the MENA region, offering programs in software development, business development, and digital marketing.

The deep-reinforcement-learning repository serves as a comprehensive resource for Udacity's Deep Reinforcement Learning Nanodegree program. It offers a collection of tutorials that guide users through the implementation of various reinforcement learning algorithms, including Dynamic Programming, Monte Carlo, Temporal-Difference, Deep Q-Networks, and Deep Deterministic Policy Gradients, all utilizing PyTorch. Additionally, the repository features labs and projects that leverage rich simulation environments from Unity ML-Agents, allowing users to train agents in tasks like navigation, continuous control, and collaborative competition. It also includes benchmarks for classic control and Box2d environments, along with detailed setup instructions for the Python environment.

Amsterdam Data Science, despite its name, functions as a review platform for online casinos, specifically those not affiliated with the Dutch Cruks exclusion system. The site offers detailed reviews and rankings of various 'No Cruks' casinos, evaluating them based on six key criteria: licensing and reliability, payout speed and limits, bonus conditions, game offerings, payment methods, and customer service. It highlights welcome bonuses, free spins, and other promotional offers, along with minimum deposit requirements and unique features of each casino. The platform aims to guide Dutch players in choosing reliable international online casinos.

Awesome-Token-Compress is a comprehensive curated list of recent research papers dedicated to token compression techniques for Vision Transformer (ViT) and Vision-Language Models (VLM). This GitHub repository serves as a valuable resource for researchers and developers interested in optimizing the efficiency of large vision-language models. It features a wide array of works, including studies on approximation-error guided token compression, dual-stage efficient token reduction, and dynamic token compression for various applications like video understanding. The collection spans papers from 2024 to 2026, highlighting advancements in areas such as spatiotemporal token merging, attention-shift-aware pruning, and reinforcement learning-guided compression, making it an essential reference for staying updated on the latest developments in the field.

GTBench is a specialized AI Agents & Automation tool hosted on Hugging Face Spaces, designed for the detailed evaluation of AI models and agents within various gaming environments. Users can interact with the application to filter and analyze performance data, making it easier to compare and understand the capabilities of different AI implementations. The platform allows for the selection of specific models, agents, and games, providing a focused view of their evaluation metrics. This tool is particularly useful for researchers, developers, and enthusiasts who need to assess and benchmark AI performance in a structured and accessible manner.

The 🐍💨 Data Contamination Database is a Hugging Face Space designed to help users identify and manage data contamination within datasets and models. This application provides functionalities to filter and view data specifically related to contamination. Users can input particular evaluation datasets and contaminated sources, and then select various options to exclude or analyze these issues. It serves as a crucial resource for AI researchers and data scientists aiming to ensure the integrity and reliability of their data, ultimately leading to more robust and accurate AI models. The tool is hosted on Hugging Face Spaces, making it accessible for a wide range of users.

Amy App is an AI-based math tutor designed to simplify mathematics for students of all levels. Acting like a real human tutor, Amy intelligently discovers and addresses individual knowledge gaps. The platform offers dynamic teaching by understanding user mistakes and automatically providing instruction on missing skills. With access to over 1.1 million unique math questions, Amy provides extensive practice and personalized learning experiences, making it an effective tool for anyone looking to improve their math proficiency and understanding.

async-rl offers a practical implementation of asynchronous 1-step Q learning, as detailed in the paper "Asynchronous Methods for Deep Reinforcement Learning." This open-source project leverages Tensorflow and Keras for deep Q network definition and optimization, while integrating with OpenAI's Gym library for interaction with the Atari Learning Environment. A key feature is its use of multiple actor-learner threads, which helps stabilize the learning process without relying on memory-intensive experience replay, making it efficient for machines with less RAM. The repository also includes a work-in-progress asynchronous advantage actor-critic implementation and provides instructions for training, visualizing with TensorBoard, and evaluating models.

AI Song and Lyrics Generator is a mobile application designed to empower users to effortlessly create original song lyrics and musical ideas. The tool utilizes smart AI technology to generate complete songs, including melodies, harmonies, and vocals, based on user-selected moods, themes, or keywords. This innovative approach significantly simplifies the songwriting process for both beginners and experienced content creators, enabling quick musical composition without requiring prior musical experience. Users can easily export their creations as high-quality MP3s, making it simple to share or further develop their musical projects. The app aims to democratize music creation by making advanced AI capabilities accessible to a broad audience.

YTGloss is a free AI browser extension designed to enhance learning from YouTube videos by providing instant, context-aware explanations. It identifies words and concepts you might not know and displays their definitions directly on the video screen, similar to a notification. This eliminates the need to pause and search for information, allowing users to stay focused on the content. The extension understands the video's subject matter, ensuring explanations are relevant (e.g., "cell" in biology vs. programming). Users can toggle video analysis on or off with a simple keyboard shortcut or through the extension menu, switching between learning and leisure modes as needed. YTGloss offers various pricing tiers, including a free plan, to accommodate different learning needs.

Deep Research by API Labz is an advanced AI tool designed to transform the research process by leveraging AI-driven analysis. It processes vast amounts of data using sophisticated algorithms to provide comprehensive and actionable insights on any research topic. Users can expect rapid results, often in minutes, instead of hours or days, with wide coverage from diverse and reliable sources worldwide. The tool offers structured reports, smart recommendations for deeper research, and visual insights through data visualizations and charts. Its advanced research suite includes unlimited queries, comprehensive report generation, multiple research perspectives, advanced AI analysis, citation support, and export capabilities, making it a complete solution for various research needs.

AnkiDroid Flashcards is a semi-official Android port of the popular Anki spaced repetition flashcard system, designed to help users efficiently memorize information. It leverages an AI-optimized FSRS algorithm to schedule flashcard reviews just before you are likely to forget them, ensuring long-term retention. The app supports various content types including text, images, and sounds, and integrates with MathJax for scientific notation. Key features include night mode, a whiteboard, progress widgets, detailed statistics, and text-to-speech integration. Users can also sync their progress with AnkiWeb for seamless cross-device study. With over 10,000 premade decks available, AnkiDroid is a powerful tool for students and anyone looking to improve their memory and learning efficiency.

Satellite-Imagery-Datasets-Containing-Ships is a comprehensive GitHub repository that curates radar and optical satellite datasets specifically designed for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datasets are invaluable for researchers and developers working in computer vision, machine learning, remote sensing, and maritime analysis. The repository details various datasets, including SSDD, OpenSARship, SAR-Ship-Dataset, AIR-SARShip, HRSID, LS-SSDD, and FUSAR-Ship, providing information on their authors, year, tasks supported, and direct access links. Each dataset entry includes specifics like image dimensions, spatial resolutions, polarization types, and annotation formats, making it a crucial resource for developing and evaluating algorithms for maritime surveillance and naval operations.

Machine-Learning-in-90-days is an open-source GitHub repository designed to guide users through learning machine learning concepts over a 90-day period. It provides a structured curriculum, including a Python crash course, to help individuals build a strong foundation in machine learning. The repository is suitable for both students and professionals looking to acquire or enhance their skills in this field, offering practical resources and a clear learning path. As a GitHub repository, it leverages the open-source community for contributions and ongoing development.

Entalpic is an AI-driven platform designed to accelerate chemistry and materials research and development, focusing on surface-driven industrial processes. It leverages cutting-edge AI, quantum modeling, and atomistic simulations to discover new materials and chemistry, enabling more sustainable industrial processes. The platform integrates multimodal datasets, including quantum simulations, scientific literature, patents, and experimental data, to power its predictive and generative models. Entalpic's technology includes a high-throughput discovery engine for screening chemical spaces, process modeling for simulating material behavior under manufacturing conditions, and a robust data curation system. It applies AI and atomic-scale modeling to solve industrial challenges in semiconductors, batteries, catalysis, and advanced materials.

machine-learning-coursera-1 is an open-source GitHub repository dedicated to housing all the coursework and assignments completed as part of Coursera's Machine Learning Course. This repository acts as a valuable resource for students and learners who wish to review, understand, or reference implementations related to the course material. It provides a structured collection of files, organized by week, covering various assignments and projects undertaken during the machine learning curriculum. The repository is publicly accessible, allowing anyone interested in machine learning to explore the practical applications and solutions developed within the course context.

UADAMAGE is an AI and GIS company specializing in geospatial analytics for automatic damage monitoring. The platform leverages satellite and drone imagery alongside advanced computer vision to assess damage following war or natural disasters. It transforms these diverse data inputs into actionable insights, aiding governments, organizations, and partners in making data-driven decisions. UADAMAGE's core focus areas include infrastructure recovery, demining efforts, and environmental monitoring, providing critical information for post-disaster assessment and planning.

TextClassification-Keras is a comprehensive code repository designed for implementing deep learning models for text classification tasks using the Keras framework. It offers ready-to-use implementations of popular models such as FastText, TextCNN, and TextRNN, making it a valuable resource for researchers and developers. The repository simplifies the application of these advanced models to text classification problems, supporting both English and Chinese documents. It serves as an excellent starting point for those looking to explore or integrate deep learning-based text classification into their projects, providing a foundational codebase for further development and experimentation.

Inverted AI develops cutting-edge AI solutions for creating highly realistic and reactive non-playable characters (NPCs) for various simulation environments. These NPCs are designed to mimic human-like behaviors, offering behavioral diversity crucial for testing and developing autonomous vehicles (AV/ADAS), autonomous robots, and smart city applications. The platform offers products like Planner and Verify, alongside Cloud API and Logs for integration. It supports different AV development stages (AV 1.0, AV 2.0, AV 3.0) and provides solutions for onboard, post-perception, and V&V (Verification & Validation) processes. Developer documentation and client libraries for C++, Python, and REST API are available, along with TorchDriveSim and TorchDriveEnv.

SAM3 Video Segmentation is an AI tool hosted on Hugging Face that provides an interactive way to perform video segmentation. Users can upload their own videos and then easily label objects within the video frames. The tool supports two primary methods for object labeling: direct clicking on the object or providing text descriptions. Once an object is labeled, SAM3 Video Segmentation intelligently tracks that object throughout the entire video, highlighting it visually. This functionality makes it a valuable resource for experimenting with and understanding AI-powered video segmentation, offering a user-friendly interface for both technical and non-technical individuals interested in computer vision applications.

The Frontier AI Cybersecurity Observatory is a platform designed to collect and evaluate AI capabilities within the cybersecurity domain. It offers a comprehensive leaderboard that allows users to explore cybersecurity data by filtering through various benchmarks and models. This tool is crucial for understanding emerging impacts and risks associated with AI in cybersecurity. Built with Gradio, it provides an interactive interface for selecting specific aspects of cybersecurity work and inputting model or agent data for evaluation.

The AI Accelerator Institute serves as an independent, knowledge-sharing platform dedicated to connecting and inspiring AI experts and machine scientists globally. It offers a community membership that provides access to a library of members-only articles, discounts on AI events, and over 250 hours of event footage. Members can join a Slack community to network with peers, exchange ideas, and discover job opportunities. The institute also hosts various events, from webinars to in-person summits, leadership dinners, and members-only meetups, designed to educate and connect professionals in the AI field. Additionally, it publishes reports, guides, and podcasts, focusing on accelerating AI at the edge and fostering the next generation of machine intelligence.