Search Results for "data processing" - Page 3
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146 projects for "data processing" with 2 filters applied:
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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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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Ai-Learn
The artificial intelligence learning roadmap compiles 200 cases
...The repository was created to help learners start self-study programs in artificial intelligence without getting overwhelmed by the large number of available resources. It organizes topics such as Python programming, mathematics for machine learning, data analysis, deep learning, computer vision, and natural language processing into a structured learning path. The project also provides a large collection of practical exercises and case studies that allow learners to apply theoretical knowledge through real projects. According to the repository description, it includes nearly two hundred hands-on AI examples developed through years of teaching experience. -
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Memori
SQL-native memory layer enabling persistent context for AI agents
Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard... -
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hls4ml
Machine learning on FPGAs using HLS
...This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. Over time, it has expanded to support a variety of scientific and industrial applications including signal processing, embedded systems, and biomedical monitoring. -
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LEANN
Local RAG engine for private multimodal knowledge search on devices
LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing... -
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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MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web... -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
...Rivet supports multiple large language model providers and integrates with services such as embeddings and transcription systems, allowing developers to create richer AI-powered features. Its architecture emphasizes composability, where different components like prompts, APIs, and data processing steps can be combined into reusable pipelines. -
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RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
RAG Web UI is an open-source intelligent dialogue system built on retrieval-augmented generation technology, designed to enable users to create AI-powered question answering systems grounded in their own knowledge bases. It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. The platform supports ingestion of multiple document formats, including PDFs, Word files, Markdown, and plain text, automatically processing and vectorizing them for efficient retrieval. It features a multi-turn conversational interface that maintains context across interactions, allowing users to engage in more natural and continuous dialogues with their data. ... -
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The Machine & Deep Learning Compendium
List of references in my private & single document
...Originally created as a personal knowledge base, the repository evolved into a public educational resource designed to help learners explore the rapidly expanding machine learning ecosystem. The compendium includes explanations of concepts across multiple domains such as natural language processing, computer vision, time-series analysis, anomaly detection, and graph learning. In addition to technical algorithms, the project also covers practical topics related to data science workflows, engineering practices, and product development in AI systems. -
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NVIDIA Generative AI Examples
Generative AI reference workflows
...The repository includes examples covering topics such as retrieval-augmented generation pipelines, agent-based workflows, and multimodal AI applications that combine text, vision, and data processing. Many of the examples show how to deploy AI services using containerized environments, GPU acceleration, and microservices that can scale across modern infrastructure. Developers can explore sample chatbot applications, document question-answering systems, and knowledge-base pipelines that illustrate how generative AI can interact with external data sources. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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Markdownify MCP Server
Convert files and web content into clean, usable Markdown easily
...By standardizing content into Markdown, it helps unify inputs across different sources for better processing and integration with AI tools and developer environments. -
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Conversational Health Agents (CHA)
A Personalized LLM-powered Agent Frameworks
...The framework supports modular components such as planning, tool execution, and multimodal input processing, which makes it suitable for complex healthcare applications. It also includes a web-based interface for interacting with the agent, making it accessible for testing and deployment in real-world scenarios. -
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Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be inserted into the notebook and executed automatically. The system uses natural language processing techniques to identify the intent of the query, extract relevant variables, and map the request to predefined code templates. ... -
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
...Through a collection of notebooks, code examples, and translated learning materials, users can explore how to implement components such as multi-head attention, data loaders, and training pipelines using Python and PyTorch. -
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ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs
ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and... -
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FlowGram
Extensible workflow development framework
...Instead of shipping as a ready-made product, it provides the building blocks — a canvas for wiring together nodes, a form engine for configuring node parameters, a variable-scope and type-inference engine, and a set of “materials” (pre-built node types such as code execution, conditional logic, LLM calls, etc.) that can be composed into larger workflows. This makes FlowGram highly flexible: you can prototype data-processing pipelines, AI-agent flows, automation scripts, or even business process automation without writing all the plumbing yourself. The framework supports both free-layout canvases (for free-form graphs) and fixed-layout canvases (for more structured flowcharts, including loops, branches, compound nodes), giving you visual freedom depending on your use-case. -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
...Many notebooks include end-to-end examples that show how to prepare input data, load optimized models, run inference, and visualize results. The project is particularly useful for developers who want to learn how to optimize machine learning inference pipelines for production environments. -
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AI Deadlines
AI conference deadline countdowns
...The repository includes configuration files and data sources that allow contributors to add or update conferences through pull requests, enabling community-driven maintenance. -
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AlphaTree
DNN && GAN && NLP && BIG DATA
AlphaTree is an educational repository that provides a visual roadmap of deep learning models and related artificial intelligence technologies. The project focuses on explaining the historical development and relationships between major neural network architectures used in modern machine learning. It presents diagrams and documentation describing the evolution of models such as LeNet, AlexNet, VGG, ResNet, DenseNet, and Inception networks. The repository organizes these architectures into a... -
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Agent SOP
Natural language workflows for AI agents
...It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. The framework supports monitoring and state tracking, so external systems can observe progress, intervene if necessary, and log outcomes for compliance or auditing. Integrations with common messaging and task orchestration systems enable SOP agents to interact with email, ticket queues, and databases as part of their workflows. -
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TADA
Open Source Speech Language Model
TADA is an open-source speech-language modeling framework designed to unify spoken audio and text representations within a single generative architecture. The system focuses on aligning speech and text streams using a dual-alignment mechanism that synchronizes the acoustic signal with its textual representation. By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This... -
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video2robot
End-to-end pipeline converting generative videos
video2robot is an end-to-end open-source pipeline that converts generative video or prompt-driven motion content into executable humanoid robot motion sequences, enabling researchers and developers to go from high-level action descriptions or videos to robot-ready motion data. The pipeline supports both prompt-to-video generation using models like Veo/Sora and video upload processing, followed by human pose extraction through a 3D pose model and retargeting of that motion to robot joints using a general motion retargeting system. This workflow allows users to generate robot motion files that specify joint angles, root positions, and orientations that can be deployed on supported robot platforms (e.g., Unitree models). ... -
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Orpheus TTS
Towards Human-Sounding Speech
...It is designed to produce human-like speech with natural intonation, emotion, and rhythm, targeting quality comparable to or better than many closed-source systems. The project ships both pretrained and finetuned English models, as well as a family of multilingual models released as a research preview, and includes data-processing scripts so users can train or finetune their own variants. Inference is provided through a Python package that uses vLLM under the hood for high-throughput, low-latency generation, including streaming examples that show how to generate audio chunks in real time. The maintainers provide Colab notebooks, a standardized prompting format, and one-click deployment via Baseten for production-grade, FP8/FP16 optimized inference with ~200 ms streaming latency. -
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goodsKill
Microservices-based flash sale system for high-concurrency testing
...It provides a unified API for testing high-concurrency seckill scenarios while demonstrating modern backend architecture patterns. goodsKill integrates key components such as Nacos for service discovery and configuration, Redis and MongoDB for data handling, and Kafka or RabbitMQ for messaging. It supports distributed transactions, database sharding, and multiple concurrency control strategies including distributed locks and message queues. It includes modular services like gateway, authentication, order management, and seckill processing, along with a Vue 3-based admin UI. ... -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and...
