Search Results for "data processing"
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Showing 2063 open source projects for "data processing"
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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Data Formulator
Create rich visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data transformation barriers via LLMs' code generation ability. ... -
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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. It begins by fetching market metadata such as questions, outcomes, and... -
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Synthetic Data Generator
SDG is a specialized framework
...It also includes a data processing module capable of handling different data types, preprocessing columns, managing missing values, and converting formats automatically before model training. -
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NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of pickups/dropoffs). ... -
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Agentic Data Scientist
An end-to-end Data Scientist
...Each agent is designed to independently call functions, interact with data sources, and adapt to uncertainties during processing, enabling iterative refinement of models without manual coordination. The framework supports interoperability with existing data tools and libraries, letting the agents leverage libraries like pandas, scikit-learn, and visualization frameworks to perform real computations rather than mock demonstrations. -
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MeshLab
The open source mesh processing system
...VCG can be used as a stand-alone large-scale automated mesh processing pipeline, while MeshLab makes it easy to experiment with its algorithms interactively. The open source system for processing and editing 3D triangular meshes. It provides a set of tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes. It offers features for processing raw data produced by 3D digitization tools/devices and for preparing models for 3D printing. -
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CyberChef
A web app for encryption, encoding, compression and data analysis
CyberChef, developed by GCHQ, is a versatile web application dubbed the "Cyber Swiss Army Knife." It enables users to perform a wide array of operations on data, including encryption, encoding, compression, and analysis, all within a browser interface. -
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Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
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pdfcpu
A PDF processor written in Go
pdfcpu is a PDF processing library written in Go supporting encryption. It provides both an API and a CLI. Supported are all versions up to PDF 1.7 (ISO-32000). This is an effort to build a comprehensive PDF processing library from the ground up written in Go. Over time pdfcpu aims to support the standard range of PDF processing features and also any interesting use cases that may present themselves along the way. The main focus lies on strong support for batch processing and scripting via a... -
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Kapacitor
Open source framework for processing, monitoring, and alerting
Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB. -
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go-streams
A lightweight stream processing library for Go
A lightweight stream processing library for Go. go-streams provides a simple and concise DSL to build data pipelines. In computing, a pipeline, also known as a data pipeline, is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. -
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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. ... -
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Arroyo
Distributed stream processing engine in Rust
Arroyo is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data. Unlike traditional batch processing, streaming engines can operate on both bounded and unbounded sources, emitting results as soon as they are available. -
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Serial Studio
Multi-purpose serial data visualization & processing
Serial Studio is a simple, multi-platform, and multi-purpose serial data visualization program that allows embedded developers to visualize, analyze, and present data generated from their projects and devices while avoiding the need to write project-specific visualization software. Over my many CanSat-based competitions, I found myself writing and maintaining several Ground Station software for each program. However, I decided that it would be easier and more sustainable to define one... -
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LAStools
efficient tools for LiDAR processing
LAStools is a collection of efficient, multi-core, scriptable tools for processing LiDAR data. It supports various formats, including LAS, LAZ, Terrasolid BIN, and ESRI Shapefiles, providing a comprehensive suite for LiDAR data management and analysis. -
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Bytewax
Python Stream Processing
...Bytewax is a Python framework and Rust distributed processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. You can use Bytewax for a variety of workloads from moving data à la Kafka Connect style all the way to advanced online machine learning workloads. Bytewax is not limited to streaming applications but excels anywhere that data can be distributed at the input and output. -
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ThingsBoard
Device management, data collection, processing and visualization
...Define relations between your devices, assets, customers or any other entities. Collect and store telemetry data in a scalable and fault-tolerant way. Visualize your data with built-in or custom widgets and flexible dashboards. Share dashboards with your customers. Define data processing rule chains. Transform and normalize your device data. Raise alarms on incoming telemetry events, attribute updates, device inactivity, and user actions. -
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jq
Lightweight and flexible command-line JSON processor
jq is like sed for JSON data - you can use it to slice, filter, map and transform structured data with the same ease that sed, awk, grep and friends let you play with text. jq is written in portable C, and it has zero runtime dependencies. You can download a single binary, scp it to a far away machine of the same type, and expect it to work. jq can mangle the data format that you have into the one that you want with very little effort, and the program to do so is often shorter and simpler... -
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Pathway
Python ETL framework for stream processing, real-time analytics, LLM
...Unlike traditional batch processing frameworks, Pathway continuously updates the results of your data logic as new events arrive, functioning more like a database that reacts in real-time. It supports Python, integrates with modern data tools, and offers a deterministic dataflow model to ensure reproducibility and correctness. -
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ExtractThinker
ExtractThinker is a Document Intelligence library for LLMs
ExtractThinker is a tool designed to facilitate the extraction and analysis of information from various data sources, aiding in data processing and knowledge discovery. -
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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cobalt
Video and media downloader: Best way to save what you love
Cobalt is an open-source media downloader and tool designed to provide a high-performance and privacy-focused alternative for interacting with online media content, particularly focused on downloading and processing media from various platforms. It emphasizes speed, reliability, and a clean user experience, allowing users to retrieve media without unnecessary tracking, ads, or intrusive elements commonly found in web-based tools. The project is built with performance in mind, leveraging efficient backend processing to handle requests quickly and consistently. ... -
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. -
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Pachyderm
Data-Centric Pipelines and Data Versioning
...Pachyderm provides a powerful solution to optimize data processing, MLOps, and ML Lifecycles.
