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Showing 109 open source projects for "processing"
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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Full-stack observability with actually useful AI | 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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Best-of Python
A ranked list of awesome Python open-source libraries
...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. -
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Dict UK
Project to generate POS tag dictionary for Ukrainian language
A Java-based tool for generating full morphological dictionaries for Ukrainian, applying affix rules to base lexemes to produce all inflected forms with part-of-speech tags—used for natural language processing and spell-checking. -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of... -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
Companion notebooks for Deep Learning is a collection of Jupyter notebooks that accompany François Chollet’s deep learning curriculum, providing hands-on implementations of key concepts using practical examples. The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. The material is designed to be accessible while still covering advanced topics, making it suitable for both beginners and intermediate practitioners. It leverages modern libraries and frameworks to demonstrate real-world applications of deep learning techniques. ... -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
Roadmap To Learn Generative AI In 2025 is a curated learning path focused on contemporary generative AI — covering large language models (LLMs), diffusion-based image generation, prompt engineering, multi-modal AI, fine-tuning techniques, and the practical considerations for deploying generative models. It’s aimed at learners and developers who already have some programming or ML basics and wish to specialize in generative AI, offering a modern, structured plan that reflects the state of the... -
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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. The repository bundles tutorials, lecture notes, project outlines, course materials, and references across topics like Python, statistics, ML algorithms, deep learning, NLP, data preprocessing, model evaluation, and real-world problem solving. ... -
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Biblatex is a LaTeX package which provides full-featured bibliographic facilities
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ChordSmith
Chordpro editor that can display, transpose and print song sheets.
ChordSmith is a chordpro editor that can display, transpose and print song sheets containing chords and lyrics. It can also edit and convert song sheet formats (including Harmonica tabs) between chordpro format (chords in square brackets in line with lyrics) and two-line format (chords above lyrics). You can find many free sources of song sheets in both formats on the Internet. More information at https://chordsmith.sourceforge.io/ Here are just a few of ChordSmith's many features: -
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SigPack
SigPack - A signal processing library using Armadillo
SigPack is a C++ signal processing library using the Armadillo library as a base. The API will be familiar for those who has used IT++ and Octave/Matlab. -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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CERCA
CERCA – Citation Extraction & Reference Checking Assistant
CERCA is an open-source research tool that supports the verification of bibliographic references in scientific manuscripts. It extracts references from PDF files and checks their existence and consistency against authoritative metadata sources, producing explainable diagnostics, audit logs, and reproducible reports. It is intended for: - Researchers performing final manuscript checks - Reviewers assessing reference consistency - Editors supporting editorial quality control -... -
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
...It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More detailed description as well as documentation can be found at webpage http://xrayutilities.sourceforge.io/. Downloads for windows can be found on http://pypi.python.org/pypi/xrayutilities Development is performed on github: https://github.com/dkriegner/xrayutilities -
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LPub3D
LDraw™ editor for LEGO® style digital building instructions.
LPub3D is an Open Source WYSIWYG editing application for creating LEGO® style digital building instructions. LPub3D is developed and maintained by Trevor SANDY. It uses the LDraw™ parts library, the most comprehensive library of digital Open Source LEGO® bricks available (www.ldraw.org/ ) and reads the LDraw LDR and MPD model file formats. LPub3D is available for free under the GNU Public License v3 and runs on Windows, Linux and macOS Operating Systems. LPub3D is also... -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
Statistics101 is an Integrated Development Environment (IDE) that uses a simple, powerful language called “Resampling Stats” to develop Monte Carlo programs to analyze and solve statistical problems. The original Resampling Stats language and computer program were developed by Dr. Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students... -
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data-science-on-gcp
Source code accompanying book: Data Science on the GCP
...It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. The repository is organized into multiple directories that reflect real-world pipelines, such as ingesting data, running SQL-based analytics, streaming data processing, using Spark and Dataproc, applying BigQuery ML, and deploying models with Vertex AI. It emphasizes practical, production-oriented workflows rather than isolated examples, showing how different Google Cloud services interact to form cohesive pipelines. -
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Flutter Tips and Tricks
A Collection of Flutter and Dart Tips and Tricks
A curated collection of over 300 Flutter and Dart tips, tricks, and code patterns shared by developer Vandad Nahavandipoor. It showcases concise, real-world examples like map equality, animations, custom errors handling, UI effects, performance tweaks, and more. This resource is excellent for both beginners and experienced developers looking to level up Flutter skills. -
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AllenNLP
An open-source NLP research library, built on PyTorch
AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
...The first half of the book introduces readers to machine learning using scikit-learn, the defacto approach for working with tabular datasets. Then, the second half of this book focuses on deep learning, including applications to natural language processing and computer vision. -
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Web based cataloging and dedupe application. Highly optimized for processing journal articles. Reads MarcXML and dedupes records using the field 773 combined with a fuzzy search on the title. Written for bibnet.org
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
...The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. Users can adapt the examples to their own data sources, financial instruments, and modeling techniques. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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Data Science at the Command Line
Data science at the command line
...To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. -
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Programa para generar documentos HTML con expresiones matemáticas incrustadas, procesadas con Maxima (maxima.sourceforge.net).
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PRMLT
Matlab code of machine learning algorithms in book PRML
...This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). ... -
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Command-Line Text Processing
From finding text to search and replace
Command-line-text-processing is a curated educational repository providing many examples and tutorials on how to use various command-line tools for processing text: searching, replacing, sorting, transforming, filtering, etc. It covers tools like grep, sed, awk, perl, Ruby one-liners, file attribute commands, sorting, tail/head/less/cat, and many more. It's intended as a learning resource, with explanations, examples, exercises, solutions. -
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A C++ library of linear algebra, signal processing and communication systems routines. This library is stand alone and it does not depend on any third party libraries indeed a C++17 compiler equipped with the standard library is necessary and sufficient. The project has been moved to https://github.com/libsusa/susa
