Research & Education

Awesome-3D-Object-Detection is a comprehensive curated list of resources dedicated to deep learning for 3D Object Detection, with a strong emphasis on lidar-based methodologies. This GitHub repository serves as an invaluable hub for researchers and engineers, providing direct links to relevant academic papers, associated code implementations, and essential datasets like KITTI, nuScenes, Lyft, and Waymo Open Dataset. It also highlights top conferences and workshops in the field, offering a structured overview of the latest developments and trends. The resource includes surveys, books, videos, and course materials, making it a one-stop reference for anyone looking to delve into or stay current with 3D object detection.

awesome-deep-learning is an extensive, curated list designed for anyone interested in Deep Learning. It serves as a central hub for discovering high-quality educational materials and community resources. The list encompasses a wide array of content, from foundational books and university courses to insightful videos, academic papers, and practical tutorials. It also highlights researchers, relevant websites, datasets, conferences, and various frameworks and tools, making it an invaluable resource for both beginners and experienced practitioners looking to deepen their understanding or find specific information within the Deep Learning domain.

Prismo is an AI-powered second brain designed to help users retain knowledge effectively. It allows users to journal their daily learnings from various sources like podcasts, books, and conversations. The tool's 'Brain Sync' AI automatically extracts key knowledge from these entries, organizing it into searchable folders and an interactive knowledge graph. To ensure long-term retention, Prismo employs spaced repetition quizzes, generating questions from the user's own knowledge base. It offers multiple quiz modes, tracks memory strength, and is available on iOS and Android, making it a comprehensive solution for personal knowledge management and memory enhancement.

Awesome-AutoDL is a comprehensive, curated list of resources dedicated to Automated Deep Learning, with a particular emphasis on Neural Architecture Search (NAS). This open-source project offers an in-depth analysis of the field, making it an invaluable resource for researchers and practitioners. It compiles links to relevant blogs, AutoDL libraries like PyGlove and AutoGluon, and various benchmarks such as NAS-Bench-101 and NATS-Bench. The list is meticulously organized by publication venues from 2017 to 2021, categorizing papers by type (gradient-based, reinforcement learning, evolutionary algorithm, performance prediction, and others), and includes direct links to code repositories where available. It serves as a central hub for staying updated on the latest advancements and foundational works in AutoDL.

ClinicTrack is a specialized software solution designed for physiotherapists to streamline their administrative tasks and enhance patient management. The platform automates the creation of clinical notes, significantly reducing the time spent on documentation. Beyond note-taking, ClinicTrack also facilitates the tracking of patient rehabilitation progress between sessions, ensuring continuous accountability and engagement from patients. This automation helps physiotherapists reclaim valuable time, allowing them to focus more on patient care rather than administrative overhead. By providing a clear overview of patient progress and accountability, ClinicTrack aims to optimize the rehabilitation process and improve overall clinic efficiency.

ExpectedEstate offers a dedicated workspace for executors to navigate the complexities of probate and estate settlement. The platform is designed to streamline the process by helping users capture essential estate information, including a comprehensive overview of assets, debts, and beneficiaries. It provides tailored checklists to guide executors through probate, trust administration, and beneficiary transfers, ensuring all necessary steps are followed. ExpectedEstate aims to foster alignment among family members during the often challenging estate settlement process, making it a valuable tool for managing legal and administrative tasks efficiently.

Awesome-Hyperbolic-Representation-and-Deep-Learning is a comprehensive repository of academic papers focusing on hyperbolic embedding, hyperbolic models, and their applications in deep learning. This resource is meticulously organized into categories such as core methods, domain applications, and task-oriented settings, making it easy for researchers to navigate the taxonomy. It highlights the natural advantages of hyperbolic spaces for processing data with tree-like structures or power-law distributions due to their exponential growth property. The repository is continuously updated with the latest research developments, including papers from major conferences like NeurIPS, ICLR, CVPR, and ACL, ensuring users have access to cutting-edge information in the field.

Khan Academy is a renowned online education platform dedicated to providing free, world-class education to anyone, anywhere. It offers a comprehensive library of lessons, practice exercises, and instructional videos covering a wide range of subjects, including math, science, humanities, and computer programming. The platform is designed to support personalized learning, allowing users to learn at their own pace and focus on areas where they need the most help. In addition to individual learners, Khan Academy provides valuable tools for teachers and parents to track student progress, assign tasks, and support educational journeys. Its mission is to make high-quality education accessible to everyone, regardless of their background or location.

awesome-ml-for-cybersecurity is a comprehensive, curated list of resources dedicated to the intersection of machine learning and cybersecurity. This open-source project serves as a valuable hub for researchers, students, and professionals looking to explore or implement ML techniques for threat detection, prevention, and analysis. The repository categorizes resources into datasets, academic papers, books, conference talks, practical tutorials, and educational courses, making it easy to navigate and find relevant information. It aims to foster development and understanding in this critical domain by providing a centralized collection of high-quality materials.

Springboard is designed to streamline preparation for meetings and workshops, offering crucial market, technological, and trend insights. This tool is particularly beneficial for professionals who need to quickly gather information before client kick-off meetings or design sprints. It helps users like Product Owners, Workshop Facilitators, Business Analysts, Design Sprinters, Product Managers, and Digitalisation/Innovation Managers to come prepared and lead effective sessions. By providing key information nuggets, Springboard aims to empower users to kick-off their engagements with confidence and expertise, ensuring they are always one step ahead.

LexLynk is a comprehensive Legal & Compliance tool designed to streamline legal research for professionals. It offers an interactive platform where users can navigate seamlessly through linked legal provisions, ensuring efficient research. Key features include a multi-column view for reading laws and texts side-by-side, direct linking of legal references, and an MS Office integration that allows users to access legal norms directly within Word and Outlook. The platform also provides a translation assistant for precise legal translations, collaborative functions for team annotations, and AI-supported analysis tools for comparing different versions of legal texts. Additionally, the LexTicker keeps users updated on current legal developments and changes.

aifeed.fyi offers a real-time AI intelligence feed, aggregating the latest developments, trends, and tools from over 270 sources. It provides a comprehensive overview of what's moving in AI, including top keywords, company trends, product updates, and trending AI models and repositories. Users can explore keyword tag trends, browse by section or topic, and view video updates related to AI. The platform is designed to keep users informed about the rapidly evolving AI landscape, ensuring they stay ahead with daily intelligence.

GoLinks search powered by ChatGPT revolutionizes internal search capabilities for businesses by integrating advanced AI. This tool allows employees to quickly locate company information and documents using natural language queries, delivering precise and contextually relevant answers. It leverages semantic and lexical analysis to suggest matches even when exact aliases are unknown, significantly improving searchability and discovery across an organization's internal knowledge base. By centralizing knowledge and reducing friction with long URLs, GoLinks enhances workplace efficiency and productivity, making it easier for teams to access shared digital resources.

Sana AI offers an AI agent designed to streamline knowledge management and interaction within organizations. This platform enables users to chat with their accumulated knowledge base, search for specific information, and interact with various data sources, including recorded meetings. It aims to enhance productivity by making information readily accessible and actionable. The tool is positioned to help individuals and teams efficiently manage and leverage their internal knowledge for better decision-making and collaboration.

awesome-multimodal-ml is a comprehensive, curated reading list designed for researchers and students interested in multimodal machine learning. Maintained by Paul Liang from CMU, this resource compiles essential papers, datasets, and course materials across various topics. It covers core areas such as multimodal representations, fusion, alignment, pretraining, and translation, alongside applications in QA, grounding, and robotics. The list also delves into advanced topics like generative learning, adversarial attacks, and bias/fairness. This GitHub repository serves as an invaluable academic resource for keeping abreast of the latest developments and foundational knowledge in the field.

Karakeep is an open-source bookmark manager designed for comprehensive digital content storage and cataloging. It allows users to quickly save links, notes, and images, which are then automatically tagged using AI for faster retrieval. Built for data hoarders, Karakeep provides a complete toolkit for organizing and rediscovering content, including collaborative lists, RSS feed integration, and a powerful rule engine for custom automation. It supports full-text search, highlights on saved pages, and offers browser extensions and native apps for seamless access. Karakeep is self-hostable with Docker, ensuring privacy and control over data, and also provides a REST API and webhooks for integration with other services.

Numberz.ai develops domain-intelligent AI systems designed for regulated and high-consequence environments where correctness and trust are paramount. The platform helps experts analyze complex documents, integrate with live enterprise systems, and process fragmented data to make critical decisions. It employs agentic intelligence, selective reasoning with large models, and domain-specific small language models (SLMs) for precision. Key features include human-in-the-loop validation, deterministic engines for grounded logic, and continuous evaluation. Built on Google Cloud, Numberz.ai offers a robust, scalable, and secure infrastructure for enterprise-grade intelligence, bridging the gap between probability and certainty in AI applications.

Data-Science-Projects is an open-source GitHub repository offering a comprehensive collection of data science projects. Each project is meticulously organized within its own directory, containing all necessary code, relevant datasets, detailed documentation, and additional resources. The repository covers a wide array of topics, including various prediction models such as Breast Cancer Prediction, Red Wine Quality Prediction, Heart Stroke Prediction, House Price Prediction, and many more. It serves as an excellent resource for students and developers looking to explore practical applications of machine learning, data analysis, and visualization techniques, providing concrete examples and results for each project.

deep-image-retrieval is an open-source project from Naver Labs Europe focused on advancing image retrieval through deep learning. It offers models and evaluation scripts implemented in Python3 and PyTorch 1.0+, enabling researchers and developers to learn deep visual representations for image retrieval tasks. The tool supports training image retrieval systems using various loss functions, including triplet loss and a novel Average Precision (AP) loss, which directly optimizes for retrieval performance. It includes pre-trained models based on Resnet architectures with different pooling mechanisms (MAC, GeM) and provides scripts for evaluating these models on standard benchmarks like Oxford5K and Paris6K, as well as for extracting features from custom image datasets.

Deep-Learning-for-Medical-Applications is a comprehensive, open-source repository on GitHub, providing a curated list of deep learning papers specifically focused on medical image analysis. This resource is designed to be a valuable starting point for researchers and practitioners in the field of medical AI. It meticulously classifies papers based on their deep learning techniques (e.g., CNN, RNN, GAN) and learning methodologies, along with metadata such as imaging modality, area of interest, and clinical database. The collection includes papers published since 2015 from peer-reviewed journals and high-reputed conferences, as well as recent arXiv preprints. The repository offers shortcuts to understand common deep learning techniques and imaging modalities, making it easier to navigate the extensive list of research.

Deeplearning-guide is a comprehensive and evolving resource designed to help individuals learn Deep Learning effectively. Inspired by Haseeb Qureshi's guide on Blockchain Development, it curates and shares valuable resources found throughout the author's own learning journey. The guide is structured into several phases, starting with prerequisites like coding and mathematics, moving through Deep Learning fundamentals, and encouraging practical application through project creation. It emphasizes a mix of theoretical understanding and hands-on coding, recommending MOOCs like deeplearning.ai and fast.ai, alongside complementary materials such as YouTube channels, blogs, and coding libraries like NumPy and Matplotlib. All recommended resources are free, making it accessible for anyone interested in diving deeper into Deep Learning.

deep_learning_object_detection is a comprehensive GitHub repository dedicated to cataloging research papers focused on object detection utilizing deep learning techniques. It serves as a valuable resource for academics and practitioners, offering an organized list of papers from 2014 onwards, including key publications from major conferences like CVPR, ICCV, and NIPS. The repository also provides links to both official and unofficial code implementations for many of the listed papers, facilitating replication and further research. Additionally, it includes performance tables comparing various detectors across different datasets like VOC and COCO, along with update logs detailing the continuous curation of new research.

dissecting-reinforcement-learning is an open-source repository offering Python code, PDFs, and supplementary resources for a series of blog posts on Reinforcement Learning. It serves as a comprehensive guide for practitioners and students, covering fundamental concepts like Markov chains, Bellman Equation, Monte Carlo methods, and Temporal Difference Learning. The repository also delves into advanced topics such as Actor-Critic methods, Evolutionary Algorithms, and various function approximation techniques including neural networks. It provides standalone Python environments for classic RL problems like the Inverted Pendulum, Mountain Car, and Multi-Armed Bandit, which do not require external installations like OpenAI Gym. This makes it an accessible resource for hands-on learning and experimentation.

Halleluyah Healthcare leverages AI, powered by JadaAI, to offer comprehensive healthcare information, integrating traditional remedies with modern health suggestions. The platform functions as a digital health companion, providing holistic guidance and facilitating connections to essential healthcare services. It is specifically designed to extend valuable health resources to underserved populations, promoting better living through accessible and intelligent health insights. The tool focuses on empowering individuals with knowledge to manage their health proactively, combining technological innovation with the wisdom of holistic traditions for a well-rounded approach to wellness.