Search Results for "collecting"
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Showing 20 open source projects for "collecting"
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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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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Chrome DevTools MCP
Chrome DevTools for coding agents
chrome-devtools-mcp is an MCP server that connects AI agents to the Chrome DevTools Protocol so they can inspect pages, record traces, read console/network data, and modify the live browser state under user control. It makes a running Chrome instance visible to MCP clients, enabling agents to debug websites end-to-end—launching Chrome, navigating, profiling, and collecting artifacts in a structured way. The repository spells out environment requirements and cautions that exposing a live browser to agents grants powerful access, so sensitive data should be handled carefully. Beyond static inspection, it exposes operational tools like starting a performance trace that an agent can later analyze to propose optimizations. ... -
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RAG-Survey
Collecting awesome papers of RAG for AIGC
RAG-Survey is an open-source research repository that collects and organizes academic papers related to retrieval-augmented generation (RAG) systems used in modern AI applications. Retrieval-augmented generation combines large language models with external knowledge retrieval systems to improve factual accuracy and contextual understanding. The repository functions as a curated catalog of research papers categorized according to a taxonomy proposed in a related survey paper on RAG methods.... -
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Agent Behavior Monitoring
The open source post-building layer for agents
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance analysis. Judgeval transforms agent interaction trajectories into structured evaluation datasets that can be used for reinforcement learning, supervised fine-tuning, or other forms of post-training improvement. ... -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
...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. The system supports real-time data streaming, allowing strategies to respond to market conditions as they evolve. QuantMuse also incorporates advanced risk management features, including portfolio monitoring, risk limits, and dynamic position sizing to control exposure. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Index
The SOTA Open-Source Browser Agent
...The project is built to integrate easily with applications through a simple programming interface, allowing developers to embed browser automation capabilities directly into their software systems. Index can perform tasks such as navigating pages, filling forms, collecting data, and analyzing web content without requiring manual scripting for each website. -
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repo2txt
Web-based tool converts GitHub repository contents
...The tool is designed to address the challenge of analyzing entire codebases with AI assistants, where code is normally distributed across many files and directories. By collecting repository contents and formatting them into a single text document, repo2txt allows developers to feed complete projects into AI systems for analysis, documentation, or code explanation tasks. The application can load repositories from platforms such as GitHub or from local directories and provides an interface for selecting which files should be included in the generated output. ... -
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LangWatch
The platform for LLM evaluations and AI agent testing
...The platform provides tools for tracking model interactions, analyzing prompt behavior, and identifying issues such as hallucinations, latency problems, or unexpected responses. By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The platform includes dashboards that visualize model behavior, enabling teams to monitor trends in response quality and reliability over time. It also provides evaluation tools that allow developers to test prompts and compare outputs across different models or configurations. ... -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
...It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. The result is a repeatable process for scoping questions, collecting evidence, and producing a concise report with citations and reasoning steps. -
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BrowserTools MCP
Monitor browser logs directly from Cursor
...It can capture console/network logs, DOM snapshots, and screenshots, and expose them as typed resources the agent can query or act on. The design aims to make IDE agents (e.g., Cursor, Claude Desktop) more “web-aware,” enabling workflows like reproducing a bug, collecting evidence, and proposing fixes without copy-pasting. Documentation and community guides outline a quick setup, including the extension, the MCP server process, and common troubleshooting steps. The project is actively maintained, with public commit activity and discussions around connectivity and reliability in different IDEs. Overall, it bridges the gap between local coding agents and the real browser they need to observe and manipulate. -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques used by high-ranking competitors. The repository also highlights important machine learning concepts such as feature engineering, cross-validation strategies, ensemble modeling, and post-processing methods commonly used in winning solutions. ... -
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AIStarter
AlStarter-Your platform for AI project management
...Packing and Sharing AIStarter excels in intelligent AI project management, offering users seamless one-click download, installation, and usage. Additionally, users have the flexibility to package projects themselves, enabling easy sharing and collecting of favorite projects. -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
...This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3 mining sites and bringing to the base. At the time the agent is born, it doesn't know how to walk nor it knows that it feels pleasure by mining. He has tact only (blind agent). The video shows learning, planning, executing and plan optimization. -
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LLMDataHub
Quick guide (especially) for trending instruction finetuning dataset
LLMDataHub is an open-source repository that aggregates and organizes datasets specifically designed for training and fine-tuning large language models. The project aims to solve the challenge of discovering high-quality datasets by collecting resources that are otherwise scattered across multiple research communities and repositories. Each dataset entry typically includes information such as size, language coverage, intended use cases, and links to the original data sources. The repository focuses particularly on datasets useful for chatbot training, instruction-following tasks, and alignment training scenarios. ... -
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NSFW Data Scraper
Collection of scripts to aggregate image data
NSFW Data Scraper is an open-source project that provides scripts for automatically collecting large datasets of images intended for training NSFW image classification systems. The repository focuses on aggregating image data from various online sources so that developers can build datasets suitable for training content moderation models. These datasets typically contain images categorized into different classes associated with adult or explicit content, which can then be used to train neural networks that detect unsafe or inappropriate material. ... -
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Top deep learning Github repositories
Top 200 deep learning Github repositories sorted by stars
...The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning, and other areas of artificial intelligence. By collecting popular open-source implementations in one place, the project simplifies the process of exploring cutting-edge tools and research implementations for deep learning practitioners. The curated lists are particularly helpful for developers who want to quickly identify well-maintained projects with strong community support. -
16
AIAlpha
Use unsupervised and supervised learning to predict stocks
...It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting market data, transforming financial indicators into machine learning features, and training models to identify patterns that may predict market trends. It also demonstrates how models can be evaluated through backtesting frameworks that simulate how a strategy would perform using historical market conditions. By combining financial analytics with machine learning algorithms, the repository illustrates the process of building data-driven investment strategies. -
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lazynlp
Library to scrape and clean web pages to create massive datasets
LazyNLP is a lightweight tool for collecting and curating large-scale text datasets for machine learning and NLP applications with minimal manual effort. -
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Meta-Learning-Papers
Meta Learning/Learning to Learn/One Shot Learning/Few Shot Learning
...The list spans topics such as gradient-based meta-learning, metric-based and relation-based methods, optimization-based approaches, and meta-reinforcement learning. By collecting these references in one place, the repository helps newcomers quickly get an overview of the intellectual history and main research directions in meta-learning. It is also useful for experienced researchers who need a convenient reference when writing surveys, proposals, or literature reviews. -
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It gives facility of collecting tweets through Twitter Streaming API w.r.t different search criteria and to save tweets in CSV and ARFF (WEKA) file formats.
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CRML - Conflict Resolution Markup Language - http://www.equiforum.org - is an open source innitiative to develop an XML based Semantic Web ontology (RDF, OWL) for researchers interested in peace to create a standard way of collecting and sharing informa
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