Search Results for "system data"
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Showing 1042 open source projects for "system data"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Synthetic Data Generator
SDG is a specialized framework
...This makes the generated data suitable for tasks such as machine learning model training, testing software systems, sharing datasets across organizations, and conducting research without violating privacy regulations. The system supports multiple generation methods including statistical models, generative adversarial networks, and large language model–based synthesis. -
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Polymarket Data
Polymarket Data Retriever that fetches, processes, and structures data
Polymarket Data is a comprehensive data engineering pipeline designed to collect, process, and structure trading activity from the Polymarket prediction market ecosystem into analyzable datasets. The system operates as a multi-stage pipeline that integrates data from both off-chain APIs and on-chain event sources, enabling users to reconstruct full trading activity including markets, order events, and executed trades. -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and generating trading signals based on quantitative models. ... -
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Data Version Control
Git-based data version control for machine learning workflows
...This approach allows teams to manage large files efficiently while maintaining a clear history of changes to data and models. DVC also provides a pipeline system that defines the stages of machine learning workflows, making experiments reproducible and easier to manage. By tracking dependencies between code, data, and parameters, the system ensures that only the necessary stages are re-run when changes occur. DVC also includes experiment tracking capabilities that allow users to compare different training runs. -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
...The system then executes those queries against a database and interprets the results, returning human-friendly insights not just raw rows, while learning from errors and successes to reduce repeated mistakes. -
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Intelligent stock analysis system
LLM-driven A/H/US stock intelligent analyzer
Intelligent stock analysis system is a Python-based smart stock analysis system that leverages large language models to automatically analyze selected equities across A-shares, Hong Kong stocks, and U.S. markets. It’s designed to produce a daily “decision dashboard” summarizing key insights such as core conclusions, precise entry/exit points, and checklists for potential trades, combining multi-dimensional technical analysis, market sentiment, chip distribution, and real-time price data. -
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Restaurant Management System
Restaurant Management System written in Python using Tkinter
...Users will have the ability to modify the data through the “Configure Facility/Menu” section of the app. Create bills for the chef (backend): The application will first send the order to the kitchen for cooks to see, prepare, and fulfill the order. -
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ShredOS
ShredOS Disk Eraser 64 bit for all Intel 64 bit processors
ShredOS is a lightweight, bootable Linux-based operating system designed specifically for secure disk erasure and data destruction. It enables users to permanently wipe hard drives, SSDs, and NVMe devices using the powerful nwipe utility and multiple industry-recognized wiping methods. Compatible with both BIOS and UEFI systems, ShredOS supports PCs, servers, and Intel-based Macs running on 32-bit and 64-bit processors. -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Elementary
Open-source data observability for analytics engineers
Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are... -
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pandas-datareader
Extract data from a wide range of Internet sources
Up-to-date remote data access for pandas. Works for multiple versions of pandas. Install using pip and then import and use one of the data readers. This example reads 5-years of 10-year constant maturity yields on U.S. government bonds. Stable documentation is available on github.io. A second copy of the stable documentation is hosted on read the docs for more details. -
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Salt
Automate the management and configuration of infrastructures at scale
Salt Bootstrap is a shell script that detects the target platform and selects the best installation method. (Supported Platforms) Your Salt master can manage itself, so a Salt minion is installed along with the Salt master. Before implementing Salt to manage any data center infrastructure it is important to understand a few things about Salt platform support including: What platforms will the Salt Master run on? What systems and infrastructure can be managed by a Salt Minion? Salt runs on and manages many versions of Linux, Windows, Mac OS X and UNIX. The Salt Supported Operating System document defines the specific operating systems that are fully supported and outlines the package creation policy for each operating system listed. ... -
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CKAN
CKAN is an open-source DMS for powering data hubs
...Around the globe, government organizations trust CKAN as their data management system of choice. CKAN is a complete out-of-the-box software solution that makes data accessible and usable – by providing tools to streamline publishing, sharing, finding and using data (including storage of data and provision of robust data APIs). CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available. -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
...The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is particularly useful in domains such as network analysis, knowledge graphs, and system architecture visualization. The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. -
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Nautobot
Network Source of Truth & Network Automation Platform
Nautobot is an open-source network source of truth and automation platform designed to manage network infrastructure data effectively. Initially built as a fork of NetBox, Nautobot extends its capabilities by offering flexible data modeling, powerful REST and GraphQL APIs, and built-in automation tools. It enables network engineers and operators to store, query, and integrate network infrastructure data with external systems, making it a key component in modern network automation workflows.... -
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WiFi DensePose
Turn WiFi signals into real-time human pose estimation and detection
WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. ... -
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Anna’s Archive
Comprehensive search engine for books, papers, comics, magazines
...It relies heavily on technologies such as Elasticsearch for search functionality and MariaDB for structured data storage, enabling fast and efficient querying across massive datasets. The system is designed with redundancy and replication in mind, allowing distributed deployments and mirrored environments to handle high traffic and large data volumes. It also includes tooling for importing datasets, managing metadata, and maintaining structured archives using custom formats. -
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Luigi
Python module that helps you build complex pipelines of batch jobs
...You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. It also comes with file system abstractions for HDFS, and local files that ensures all file system operations are atomic. -
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ArchiveBox
Open source self-hosted web archiving
ArchiveBox is a powerful, self-hosted internet archiving solution to collect, save, and view websites offline. Without active preservation effort, everything on the internet eventually disappears or degrades. Archive.org does a great job as a centralized service, but saved URLs have to be public, and they can't save every type of content. ArchiveBox is an open source tool that lets organizations & individuals archive both public & private web content while retaining control over their data.... -
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich... -
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SearXNG
Free internet metasearch engine which aggregates
...Instead of maintaining its own index, it queries numerous external search providers and merges the results into a single interface, increasing coverage and diversity of information. One of its core principles is privacy, as it does not track users, store personal data, or create search profiles, making it a strong alternative to traditional search engines. . The system can be self-hosted, allowing individuals or organizations to run their own private search instance with full control over configuration and data handling. It supports extensive customization, including selecting which engines to query, filtering content, and adjusting ranking or display behavior. ... -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative)... -
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. The core concept of the framework is the use of semantic operators, which extend traditional relational database operations to support reasoning over text and other unstructured data. -
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RecoverPy
Interactively find and recover deleted or overwritten files
RecoverPy is a powerful tool that leverages your system capabilities to recover lost files. Unlike others, you can not only recover deleted files but also overwritten data. Every block of your partition will be scanned. You can even find a string in binary files. -
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mosaicml composer
Supercharge Your Model Training
composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for...
