Data & Analytics

MarketAlerts.ai provides proprietary datasets, market indicators, and Key Opinion Leader (KOL) networks to drive growth in the fintech sector. The platform offers on-chain, off-chain, and alternative data engineered for alpha discovery and rigorous backtesting. Users can access battle-tested market indicators built by quants, delivered via API, dashboards, or webhooks. MarketAlerts also provides direct access to a curated network of crypto and fintech KOLs across various regions. Beyond data, it offers full-stack growth strategy for finance brands, including positioning, performance, content, and community, alongside product development services for trading infrastructure, dashboards, smart contracts, and market-grade UIs. Advisory and research services, including token design and go-to-market frameworks, are also available.

synthetic-computer-vision is a GitHub repository dedicated to tracking and organizing resources related to the use of synthetic images in computer vision research. It serves as a valuable hub for researchers, offering a curated list of synthetic datasets such as SunCG, Minos, and Synthia, alongside various tools like AirSim, CARLA, and UnrealCV. The repository also includes a collection of relevant academic publications, categorized by year, with links to papers, code, and project pages. Users are encouraged to contribute by adding missing works or updating existing information through pull requests, making it a collaborative and up-to-date resource for the computer vision community.

WebWorldWind is an Open Source JavaScript SDK developed by NASA, with contributions from the European Space Agency, designed for creating geo-browser web applications. It allows developers to embed a 3D globe directly into HTML5 web pages, providing a geographic context with terrain and various shapes for displaying and interacting with geo-located information in both 3D and 2D. The SDK automatically retrieves high-resolution terrain and imagery from remote servers as needed, while also supporting custom terrain, imagery, 3D shapes, and position markings. Key features include improvements to COLLADA 3D model support, the ability to obtain click locations in 3D models, and enhanced Well-Known Text format support. It is licensed under the Apache License, Version 2.0.

TheWell is a data visualization tool hosted on Hugging Face Spaces, designed for exploring and visualizing physics simulation datasets. Users can select a dataset, a specific field within that dataset, and a file to view the corresponding data. A key feature is the ability to adjust time steps, which is particularly useful for analyzing dynamic fields within the simulations. This tool is ideal for researchers, students, and data scientists working with physics simulation data, offering an intuitive interface for data exploration and analysis directly within the Hugging Face ecosystem. It simplifies the process of interacting with complex scientific datasets.

Hub LFS Analysis is a specialized tool designed to provide in-depth insights into Git Large File Storage (LFS) usage within the Hugging Face Hub. It offers comprehensive visualizations and tabular data to help users understand their LFS storage growth over time. The application breaks down file sizes by extension, allowing for a clear overview of data distribution. A key feature is its ability to identify potential storage savings through file-level deduplication, which can be invaluable for optimizing storage and cost efficiency. This tool is particularly useful for data scientists and AI researchers managing large datasets on the Hugging Face platform.

Grounding DINO 1.5 API introduces a suite of advanced open-set object detection models developed by IDEA Research, pushing the boundaries of open-set object detection. The suite includes Grounding DINO 1.5 Pro, designed for stronger generalization across a wide range of scenarios, and Grounding DINO 1.5 Edge, optimized for faster speed in edge computing applications. The project provides examples for using these models, which are hosted on DeepDataSpace. Users need to apply for an API Token through the DeepDataSpace website for their first application and can purchase additional API calls. The models demonstrate state-of-the-art performance on various benchmarks, including COCO, LVIS, and ODinW, for zero-shot and few-shot transfer learning.

Object-Detection-Metrics is an open-source toolkit designed to provide comprehensive metrics for evaluating object detection algorithms. It addresses the lack of consensus and standardized implementations for these metrics, offering a reliable solution for researchers and developers. The tool includes implementations for popular metrics such as Intersection Over Union (IOU), Precision, Recall, Precision x Recall curve, and Average Precision (AP), including both 11-point and all-point interpolation methods. It simplifies the evaluation process by accepting ground truth and detected bounding boxes without requiring complex file conversions. The implementation has been carefully compared against official versions, ensuring accurate and trustworthy results for benchmarking different approaches.

SINet is an open-source project for Camouflaged Object Detection (COD), a challenging computer vision task focused on detecting objects that blend into their natural habitat. Developed by Deng-Ping Fan and colleagues, SINet was presented at CVPR 2020 (Oral) and offers a robust baseline for COD research. The repository includes detailed introductions, the Search & Identification Net (SINet) model, and one-key evaluation codes. It also features the COD10K dataset, which provides diverse and meticulously annotated samples for training and testing. SINet is implemented in PyTorch and supports both training and testing, with an enhanced version (SINet-V2) accepted at IEEE TPAMI 2022. The project also highlights potential applications in medical imaging, agriculture, art, and computer vision.

TradingView is a comprehensive platform designed for traders and investors to track and analyze global financial markets. It provides advanced charting tools, real-time quotes, and a social network where users can share and discuss trading ideas. The platform supports a wide range of assets including stocks, forex, cryptocurrencies, and economic indicators. Users can access community-generated ideas, indicators, and strategies, making it suitable for both beginners and experienced market participants. TradingView offers various paid plans with increasing features and data access, and allows for secure payments including credit cards, PayPal, Apple Pay, and cryptocurrency.

splatviz is a comprehensive, open-source Python-based interactive viewer designed for real-time editing and analysis of 3D Gaussian Splatting scenes. Utilizing the pyimgui GUI library, it enables direct manipulation of Gaussian Python objects just before rendering, offering extensive editing and visualization capabilities. Users can view multiple scenes simultaneously, either side-by-side or in a split-screen view, and evaluate Python expressions on the resulting scene. Key features include an Edit Widget for real-time manipulation of Gaussian parameters, an Eval Widget for debugging and visualizing variables, and a Camera Widget with Orbit and WASD modes for flexible scene navigation. It also supports attaching to running 3DGS training sessions for live inspection and editing.

tensor-house offers a comprehensive toolkit for rapid readiness assessment, exploratory data analysis, and prototyping diverse modeling approaches within enterprise AI/ML/data science projects. It includes Jupyter notebooks and demo AI/ML applications tailored for specific business needs such as marketing, pricing, supply chain, and smart manufacturing. This resource is designed to help developers and data scientists quickly build and deploy intelligent applications, manage and compare prompts, and integrate external tools. It also provides features for automating workflows, managing code changes, and securing applications, making it a versatile platform for developing and deploying AI solutions.

MMDetection3D is an open-source object detection toolbox built on PyTorch, designed as OpenMMLab's next-generation platform for general 3D detection. It supports a wide range of multi-modality and single-modality detectors, including MVXNet, VoteNet, and PointPillars. The platform handles popular indoor and outdoor 3D detection datasets like ScanNet, SUNRGB-D, Waymo, nuScenes, Lyft, and KITTI. A key feature is its natural integration with MMDetection, allowing users to leverage over 300 models and methods from 40+ papers in 2D detection. MMDetection3D is known for its high efficiency, offering faster training compared to other codebases, making it a robust library for various 3D detection projects.

NewsMaker 23 is a comprehensive market and economic intelligence platform designed to provide users with real-time news, in-depth analysis, and critical data across various financial sectors. The platform covers market news, cryptocurrency, indices like Nikkei and Hangseng, commodities such as gold, silver, and oil, and major currencies. It offers an economic calendar, live charts, historical data, and tools like Pivot & Fibonacci for technical analysis. NewsMaker 23 also features market and economic intelligence insights, including analysis and opinions on global events, market developments, and fiscal policies. The platform emphasizes educational content and aims to deliver fast, accurate, and user-friendly financial information.

Unsupervised-Classification is a GitHub repository offering a PyTorch implementation of the paper "SCAN: Learning to Classify Images without Labels." This tool addresses the challenge of automatically grouping images into semantically meaningful clusters when ground-truth annotations are absent. It deviates from recent end-to-end approaches by advocating a two-step method where feature learning and clustering are decoupled. The project demonstrates significant performance improvements over state-of-the-art methods on various benchmarks, including CIFAR10, CIFAR100-20, STL10, and ImageNet. It provides code for pretext tasks (like SimCLR), clustering (SCAN), and self-labeling steps, along with pretrained models and evaluation scripts, making it a valuable resource for researchers in computer vision and unsupervised learning.

F/AI is a personal AI fitness trainer designed to help users achieve muscle gain, weight loss, strength building, or general fitness. It offers personalized AI workout plans tailored to individual goals, body metrics, and limitations, considering factors like experience, equipment, health issues, and sleep quality. The tool includes an AI chat feature for instant responses to questions about technique, nutrition, and recovery, remembering context for ongoing guidance. Users can also utilize photo body analysis to determine body type, fat percentage, and measurements, receiving personalized recommendations. F/AI supports workouts at home, in the gym, or outdoors, with smart exercise replacement features to adapt plans based on available equipment or physical limitations. It tracks progress through workout logging and body analysis, making it a comprehensive solution for personalized fitness.

Google Earth is a powerful data visualization tool that allows users to explore the world from their device. It provides high-resolution satellite imagery and immersive 3D terrain, enabling virtual travel to any location globally. Users can view cities in 360° Street View, offering a detailed perspective of various environments. The platform also supports the creation of personalized maps with placemarks and photos, making it a versatile tool for geographical discovery and visualization. It offers a unique way to understand global landscapes and urban areas, providing rich visual data for exploration and analysis.

Free IP API offers a robust and reliable IP geolocation service designed for developers requiring fast and accurate IP lookup capabilities. This API allows users to transform any IP address into detailed location information, including country, city, region, postal code, ISP, timezone, and currency. With ultra-low latency (sub-15ms average) and a global edge network, it ensures real-time performance and seamless integration into various applications. Developers can leverage Free IP API for use cases such as fraud detection, content localization, geo-targeting, analytics, and enhancing user experience by tailoring services based on geographical data. It provides a powerful solution for businesses and individual developers needing precise geographical insights from IP addresses without significant cost or complexity, supporting both single and bulk IP lookup operations.

MetalPrices.live offers real-time precious and base metals prices, including Gold, Silver, Platinum, Palladium, Copper, Aluminum, Nickel, and Zinc, from 7 global exchanges like COMEX, London, and Shanghai. It provides institutional-grade market data such as COMEX futures delivery activity, CFTC Commitments of Traders (COT) reports, and vault inventory levels from COMEX, LBMA, and SHFE. Users can access bank analyst price forecasts, a macro economic dashboard, and AI-generated market commentary. The platform supports over 30 currencies and unit conversions, allowing for comprehensive market analysis and tracking of physical vs. futures dynamics, all completely free with no account required.

ReportCraft streamlines the creation of Splunk dashboards, reports, and alerts by converting natural language requests into import-ready configurations. Users describe their needs in plain English, and the tool generates the necessary SPL queries and exportable assets. This eliminates hours of manual configuration work and bridges the gap between business stakeholders and data engineers. It supports prototyping with field names, CSV uploads for richer type detection, or manual field pasting. ReportCraft focuses on being Splunk-first, ensuring high-quality, reviewable outputs without direct connection to your Splunk instance, maintaining user control over deployment.

StatsHub.ai is a market research tool designed to provide instant, structured reports with regional breakdowns and competitive tables. Users can enter a market keyword or topic, and the AI generates a comprehensive analysis, including executive summaries, global market overviews, region-level analysis (Americas, APAC, Europe, MEA), drivers and barriers, distribution channels, buyer segments, market segmentation, key player profiles, and competitive benchmarking. The reports are available for $49 and can be downloaded instantly in PDF and editable formats. A free preview is available to review the report structure before purchase, making it ideal for fast market decisions and sanity checks.

Mango Media is a web design and SEO agency based in Niagara, specializing in helping local businesses improve their online presence. They offer comprehensive SEO services aimed at getting clients ranked on Google Maps and local search results, leading to more clicks and calls. Beyond SEO, Mango Media designs professional, mobile-responsive websites that are optimized for search engines, ensuring businesses are easily found by their target audience. The team emphasizes clear communication and a results-driven approach, working closely with clients to understand their goals and deliver tangible growth. They aim to make the process of improving online visibility straightforward and effective for businesses.

avod is an open-source implementation of the Aggregate View Object Detection (AVOD) network, specifically designed for 3D object detection in autonomous driving scenarios. This repository offers a Python-based solution for researchers and developers to implement and experiment with advanced 3D object detection algorithms. It leverages view aggregation techniques to enhance detection accuracy. The project includes detailed instructions for setting up the environment, installing dependencies, configuring training parameters, and running evaluations on datasets like KITTI. It also provides pre-trained models and scripts for visualizing results, making it a comprehensive resource for those working in the field of autonomous vehicle perception.

Bemi IO offers an automatic audit trail solution for PostgreSQL databases, designed to track and record data changes with 100% reliability and accuracy. It integrates seamlessly with existing PostgreSQL databases in minutes, requiring no write permissions. The tool automatically enriches low-level data changes with application context, such as the API endpoint, user, or cron job responsible for the change. Bemi ensures data security with military-grade encryption for data at rest and in transit, and customer-level isolation. Data is stored in an auto-scaled, optimized serverless PostgreSQL database, allowing for time travel queries and integration with ORMs. It is ideal for audit and compliance, observability, troubleshooting, data recovery, and building activity feeds.

Awesome-Referring-Image-Segmentation is a curated GitHub repository that compiles a vast collection of academic papers and datasets related to referring image segmentation. This resource is invaluable for researchers and practitioners in the computer vision domain, offering insights into traditional and interactive methods, as well as current challenges in the field. The repository is organized into sections covering datasets, challenges, traditional referring image segmentation, interactive referring image segmentation, referring video object segmentation, 3D referring segmentation, and referring image segmentation in specific domains. It is actively maintained and encourages contributions via pull requests or issue submissions, fostering a collaborative environment for advancing research in this specialized area.