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Analytics Engine combines PostgreSQL, n8n and Metabase to collect and analyze market data. The repository includes a Docker Compose environment and setup instructions.
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GitHub collection of APT reports, threat actor notes, and security research documents.
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This is a curated gallery of interesting Jupyter Notebooks, organized by topic categories including introductory tutorials, programming and computer science, statistics and machine learning, data science, mathematics, physics, chemistry, biology, earth science, geo-spatial data, linguistics, and text mining.
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Code for Data Science at Olin College, Spring 2014.
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Applied ML is a curated collection of papers, articles and blogs about data science and machine learning in production, organized under topics such as data quality, recommendation, search and ranking, and MLOps. It is licensed under MIT and covers how organizations frame problems and which techniques worked.
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) - RSS/Atom gateway to Nostr. Live at [https://atomstr.data.haus](https://atomstr.data.haus)
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Awesome DataHoarding is a GitHub repository that maintains a curated list of tools related to data hoarding. The project collects utilities for storing, backing up, and managing large amounts of data. It is community-driven and open for contributions.
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Bread Dataset Viewer is a VS Code extension for viewing and handling large datasets. It opens JSONL, Parquet, CSV, TSV, JSON, and Arrow/Feather files by streaming and lazy-loading data, and provides Cards, Table, and Raw views. It includes 16 production LLM tokenizers from GPT, Claude, Llama, and Qwen for chat completion data.
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Changd is an open source, self-hosted web monitoring application and a free alternative to SaaS-based solutions. It monitors visual site changes using differential screenshots, XPath expressions or data returned from API endpoints. The frontend uses TypeScript, React and AntD, the backend runs on Node.js, and data is persisted in a Postgres database.
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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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Open-source Python library for data-centric AI that helps clean data and labels by automatically detecting issues in machine learning datasets. It uses existing models to estimate dataset problems that can be fixed to train better models. It runs on Python 3.10+ and works with any model across classification, regression, segmentation and object detection tasks.
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) - DVM documentation and kind registry
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Official PyTorch implementation of the CVPR 2019 paper on deep high-resolution representation learning for human pose estimation. The network maintains high-resolution representations through the whole process and connects multi-resolution subnetworks in parallel with repeated multi-scale fusions. Results are reported on the COCO keypoint detection dataset and the MPII Human Pose dataset.
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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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Evidently is an open-source observability framework for machine learning and large language models, hosted on GitHub under the evidentlyai organization. It enables users to evaluate, test, and monitor AI-powered systems and data pipelines, with support for use cases ranging from tabular data processing to generative AI, and includes more than 100 built-in metrics.
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Exploit-DB paper archive with security research, exploitation papers, and technical writeups.
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Facets is a project containing two visualizations, Facets Overview and Facets Dive, for understanding and analyzing machine learning datasets. The visualizations are Polymer web components backed by TypeScript that can be embedded in Jupyter notebooks or webpages. Overview produces feature-by-feature statistical analysis and compares statistics across datasets. The repository was archived on Jul 27, 2024 and is now read-only.
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FATE (Federated AI Technology Enabler) is an industrial grade federated learning open source framework that enables enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation, and provides federated learning algorithms including logistic regression, tree-based algorithms, deep learning and transfer learning.
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Gaussian Mixture Model is an unsupervised machine learning implementation using a multivariate Gaussian mixture model. It supports both offline data and real-time data streams. The repository provides installation instructions, a simple example, and a license. It is hosted on GitHub at https://github.com/lukapopijac/gaussian-mixture-model.
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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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A repository holding the winning solution for the Galaxy Challenge on Kaggle. It includes code, documentation and data files, with instructions for installing dependencies such as Theano and pylearn2, downloading training data and generating the solution file.