Search Results for "data processing"
Sort By:
Showing 41 open source projects for "data processing"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
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. -
2
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... -
3
SLAM in Autonomous Driving Book
SLAM Technology in Autonomous Driving
SLAM in Autonomous Driving Book is the open-source code companion to the book SLAM in Autonomous Driving. It focuses on localization and mapping systems that combine LiDAR, IMU, GNSS, and vehicle motion data. The material begins with geometry, kinematics, Kalman filtering, inertial navigation, preintegration, and graph optimization. It then implements point-cloud processing, nearest-neighbor structures, ICP, NDT, scan matching, occupancy grids, and loop closure. Readers build both loosely coupled and tightly coupled LiDAR-inertial odometry systems. ... -
4
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. -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
5
Biblatex is a LaTeX package which provides full-featured bibliographic facilities
-
6
xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. 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). ... -
7
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... -
8
data-science-on-gcp
Source code accompanying book: Data Science on the GCP
The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. 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. ... -
9
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... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
10
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
-
11
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. -
12
Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
...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. -
13
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). ... -
14
lottie vectors
Create, display and process 2D vectors in a 3D window.
Lottie Vectors is an application for Matlab that alows you to do some pretty neat things -with vectors. More exactly -displaying them in ways that hopefully will allow you to explore and better understand your vector data. The basic idea is simple, take a vector defined in one of a few different types of data formats and map it on the screen. Add another vector and you start to form a 'route'. Each route or position vector can be accompanied with a 'force' vector. This can be used to... -
15
TESTIMAGES
Testing images for scientific purposes
...Please cite the following papers when using any image in this archive: * ASUNI N, GIACHETTI A, "TESTIMAGES: A Large Data Archive For Display and Algorithm Testing", Journal of Graphics Tools, Volume 17, Issue 4, 2015, pages 113-125, DOI:10.1080/2165347X.2015.1024298 * ASUNI N, GIACHETTI A, "TESTIMAGES: a large-scale archive for testing visual devices and basic image processing algorithms", STAG - Smart Tools & Apps for Graphics Conference, 2014. -
16
-
17
Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
OCL stands for Open Cezeri Library (yet another linear algebra and matrix library). This library provides rapid coding as matlab ease of use. To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1-... -
18
MARC/Perl
Perl libraries for processing MARC records
MARC/Perl (formerly known as MARC.pm) is a project to develop Perl libraries to process MARC (MAchine Readable Cataloging) data. -
19
WebDjVuTextEd
Edit the OCR text layer of DjVu documents in a web browser
WebDjVuTextEd allows to edit the text layer of OCR'ed DjVu documents in a web browser. You can modify the structure (paragraphs, lines, words...) create, delete, edit text nodes, modify their container box by mouse, and run a spellchecker. The program does not directly read the DjVu files, it requires exported XML text data and images. When using without a webserver, you can open and save local files, but cannot take advantages of auto-save and spell checking. Note that current SVN... -
20
Yes, finally. The author decide to schedule some of his busy time to release the "Chinese Language Formula"- Step By Step. It will take a while, but eventually Chinese Language Processing is no longer a problem.
-
21
ExData Plotting1
Plotting Assignment 1 for Exploratory Data Analysis
...The dataset covers nearly four years of minute-level measurements, including power consumption, voltage, current intensity, and detailed sub-metering values for different household areas. For analysis, focus is placed on a two-day period in February 2007, highlighting short-term consumption trends. The data requires careful handling due to its size of more than 2 million rows and coded missing values. By processing the date and time fields into proper formats, it becomes possible to generate clear time-series plots of energy usage. The repository demonstrates effective exploratory data analysis practices in R with a reproducible workflow for transforming raw data into visual insights. -
22
Large Text File converter
Java Based Heavy-duty utilitity to process large delimited text files
TextZilla is a Multithreaded Java utility which can process huge size delimited text files to extract, convert, encode, decode, encrypt/decrypt text data from source and write it in desired output file or files. It provides fully extensible framework based on which Java classes can be created, for example it currently has MD5 conversion capability, based on same design classes for 3DES ,AES or any other Algo can be created. Another strength of this tool is in its configurability, it's... -
23
Cracker-ng
Cracker-ng is a multiple file password finder.
/!\ Developer(s) needed to optimize routines, multi-processing; any kind of help is accepted :) -
24
BotoSeis
This version is deprecated
BotoSeis is a collection of interactive Java programs for seismic data processing. It may work also as a graphical user interface for packages like CWP/SU (Seismic Un*x), Madagascar and user home made programs. A new version is available at: https://github.com/botoseis/BotoSeis You can find a user guide at: https://germangarabito.wordpress.com -
25
A java library for the processing and analysis of natural language texts and other sequential data. The focus is on unsupervised modeling with simple, statistical methods as well as implementations of more complex algorithms.
