Search Results for "jpk data processing"
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Showing 1230 open source projects for "jpk 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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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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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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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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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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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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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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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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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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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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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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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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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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Broadway
Concurrent and multi-stage data ingestion and data processing
Broadway is a data processing library for Elixir designed to handle high-throughput, concurrent workloads with ease. It provides an abstraction for defining pipelines that consume data from sources like RabbitMQ, Kafka, Amazon SQS, or custom producers. Each pipeline is fault-tolerant and backpressure-aware, ensuring stable throughput even under load. -
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HDF5
Official HDF5® Library Repository
HDF5 (Hierarchical Data Format v5) is a widely-used data management library and file format for storing large and complex scientific data sets efficiently. -
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EEGLAB
EEGLAB is an open source signal processing environment
EEGLAB is an open source, MATLAB-based interactive environment for analyzing electrophysiological signals such as EEG and MEG. It incorporates powerful tools for data import, preprocessing, independent component analysis (ICA), time-frequency analysis, artifact rejection, and visualization—all within a GUI framework that also supports scripting and plugin extensions. EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command line only for Octave). ... -
19
GLM
OpenGL Mathematics (GLM)
...This project isn't limited to GLSL features. An extension system, based on the GLSL extension conventions, provides extended capabilities: matrix transformations, quaternions, data packing, random numbers, noise, etc. This library works perfectly with OpenGL but it also ensures interoperability with other third party libraries and SDK. It is a good candidate for software rendering (raytracing / rasterisation), image processing, physics simulations and any development context that requires a simple and convenient mathematics library. ... -
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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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Pachyderm
Data-Centric Pipelines and Data Versioning
...Pachyderm provides a powerful solution to optimize data processing, MLOps, and ML Lifecycles. -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. ... -
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Best-of Python
A ranked list of awesome Python open-source libraries
...Ranked list of awesome python libraries for web development. Correctly generate plurals, ordinals, indefinite articles; convert numbers. Libraries for loading, collecting, and extracting data from a variety of data sources and formats. Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks.
