Search Results for "text batch processing tools"
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Showing 14 open source projects for "text batch processing tools"
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Pathway
Python ETL framework for stream processing, real-time analytics, LLM
...Pathway is especially well-suited for scenarios like financial analytics, IoT, fraud detection, and logistics, where high-velocity and continuously changing data is the norm. 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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Scanopy
Clean network diagrams, One-time setup, zero upkeep
Scanopy is a powerful multi-modal data capture and analysis toolkit that enables users to collect, process, and visualize structured and unstructured information from a variety of sources in a flexible pipeline. It is built to handle complex scanning tasks — such as OCR, document analysis, audio transcription, network data capture, and image extraction — while providing unified APIs and workflows that make managing heterogeneous data sources seamless. Developers can compose custom pipelines... -
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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... -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. -
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Stand-alone application and Python tools for interactive and/or batch processing analysis of X-Ray Fluorescence Spectra. Graphical user interface (GUI) and batch processing capabilities provided.
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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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text-dedup
All-in-one text de-duplication
text-dedup is a Python library that enables efficient deduplication of large text corpora by using MinHash and other probabilistic techniques to detect near-duplicate content. This is especially useful for NLP tasks where duplicated training data can skew model performance. text-dedup scales to billions of documents and offers tools for chunking, hashing, and comparing text efficiently with low memory usage. It supports Jaccard similarity thresholding, parallel execution, and flexible... -
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Amadeus
Harmonious distributed data analysis in Rust
Amadeus is a high-performance, distributed data processing framework written in Rust, designed to offer an ergonomic and safe alternative to tools like Apache Spark. It provides both streaming and batch capabilities, allowing users to work with real-time and historical data at scale. Thanks to Rust’s memory safety and zero-cost abstractions, Amadeus delivers performance gains while reducing the complexity and bugs common in large-scale data pipelines. -
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Luminance HDR
Complete solution for HDR photography
Luminance HDR is a complete suite for HDR imaging workflow. It provides a wide range of functionalities, during both the fusion stage and the tonemapping stage. Its graphical user interface, based on Qt5, runs on a variety of platforms, such as Microsoft Windows, Mac OS X 10.9 and later and several Unix flavors (Linux, FreeBSD and others). Input images can be supplied in multiple formats, from JPEG to RAW files. In the same way, output can be saved in many different formats as well, from... -
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Data Science at the Command Line
Data science at the command line
Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. ... -
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SIVIC is an open-source, standards-based software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.
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iMir
Integrated pipeline for HT miRNA-Seq data analysis
Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. -
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A MATLAB package for wavelet analysis of circadian rhythms with both discrete (Daubechies) and continuous (Morlet) wavelets, as well as tools for batch processing of multiple time series, all accessible through a graphical user interface.
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Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.
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