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Open source utility to manage Steam, Origin and Uplay libraries in ease of use with multi library support. ||| Steam Games Database: https://stmstat.com
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Steganography extraction tool for finding hidden files or data inside images.
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Python steganography tool for hiding or extracting data in supported image and audio files.
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Telegram-focused OSINT toolbox with resources for researching accounts, channels, and public data.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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The open source standard for data logging. Enables ML monitoring and observability.
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Code for Data Science at Olin College, Spring 2014.
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) - RSS/Atom gateway to Nostr. Live at [https://atomstr.data.haus](https://atomstr.data.haus)
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Project that automatically maps relationship networks by parsing public data using LLMs and visualizes it as an interactive graph.
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Python library for data-centric AI and machine learning with messy, real-world data and labels.
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Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science.
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) - DVM documentation and kind registry
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Interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security.
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Datamining Discord changes from the JS files
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Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform.
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DVMCP is a bridge implementation that connects Model Context Protocol (MCP) servers to Nostr's Data Vending Machine ecosystem
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Eurybia monitors data and model drift over time and securizes model deployment with data validation.
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Python package for geospatial intelligence workflows, location data, and map-based OSINT tasks.
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Google Advanced Data Analytics Projects: Automatidata, Waze, Tiktok and Salifort Motors
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Provides a central interface to connect your LLM's with external data.
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LlamaIndex is a data framework for your LLM applications.
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Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.
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Peer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft.
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Synthetic tabular data generation using GANs, Diffusion Models, and LLMs with adversarial filtering and privacy metrics.