Search Results for "big data visualization" - Page 32
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Showing 2803 open source projects for "big data visualization"
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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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geometry-api-java
The Esri Geometry API for Java enables developers to write apps
The Esri Geometry API for Java can be used to enable spatial data processing in 3rd-party data-processing solutions. Developers of custom MapReduce-based applications for Hadoop can use this API for spatial processing of data in the Hadoop system. The API is also used by the Hive UDF’s and could be used by developers building geometry functions for 3rd-party applications such as Cassandra, HBase, Storm and many other Java-based “big data” applications. -
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WebVisu
Pure Browser based Visualisation for PLCs
Framework to enable PLC Visualisations (like Wago 750-841, Beck IPC, CoDeSys 2.3) displayed in a standalone Browser without Java applets. Including Browsers of iPad, iPhone, iPod, Android aso.. Based on HTML5 canvas and Javascript. -
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OpenFrames
Real-time interactive 3D graphics API for scientific simulations
OpenFrames has moved its primary development repository to GitHub! Everything else will follow. Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently... -
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ArrayFire.jl
Julia wrapper for the ArrayFire library
ArrayFire is a library for GPU and accelerated computing. ArrayFire.jl wraps the ArrayFire library for Julia, and provides a Julia interface. Install ArrayFire library: either download a binary from the official site, or you can build from source. -
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ClimateMachine.jl
Earth System Model that automatically learns from data
The ClimateMachine is a software package that models the evolution of the Earth system over weeks to centuries. The ClimateMachine solves three-dimensional partial differential equations for the distributions of water, momentum, energy, and tracers such as carbon in the atmosphere, oceans, and on land. The ClimateMachine will harness a wide range of Earth observations and data generated computationally to predict the evolution of Earth’s climate and features such as droughts, rainfall... -
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ElectronDisplay.jl
An Electron.jl based figure and table display.
This package provides a display for figures, plots and tables. When you load the package, it will push a new display onto the Julia display stack and from then on it will display any value that can be rendered as png, svg, vega, vega-lite or plotly in an electron-based window. This is especially handy when one works on the REPL and wants plots or tables to show up in a nice window. -
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Jupytab
Display in Tableau data from Jupyter notebooks
Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab. -
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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eMatrix
A C++ Matrix Library
eMatrix is a lightweight matrix library developed in C++. EMatrix is designed to help solve engineering problems requiring linear algebra. eMatrix is OS independent and is fairly portable. New features include inv(A) and det(A). -
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JuliaDB.jl
Parallel analytical database in pure Julia
JuliaDB is a package for working with large persistent data set. JuliaDB provides distributed table and array datastructures with convenient functions to load data from CSV. JuliaDB is Julia all the way down. This means queries can be composed with Julia code that may use a vast ecosystem of packages. -
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OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
OzGIS is an extensive mapping system for the analysis and display of geographically referenced data. Map data are downloaded from Census bureaux and map agencies or extracted from your own databases. The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research. Systems for Windows, Mac and Ubuntu, source code, sample data files and manuals are included. DOWNLOAD to... -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own... -
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Limada (Linked Marked Data) is a framework for managing relationships of data in non-hierarchical structures, where the individual elements are interconnected in complex ways. The philosophy behind: Information is connection, is relationship of data.
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IPyPublish
Workflow for creating and editing publication ready scientific reports
A program for creating and editing publication-ready scientific reports and presentations, from one or more Jupyter Notebooks. Dynamically (and reproducibly) explore data, run code, and output the results. Dynamically edit and visualize the basic components of the document (text, math, figures, tables, references, citations, etc). Have precise control over what elements are output to the final document and how they are layed out and typeset. Also be able to output the same source document to... -
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ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
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NLOptControl.jl
nonlinear control optimization tool
This software solves nonlinear control problems at a high level very quickly. -
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CUDAnative.jl
Julia support for native CUDA programming
The programming support for NVIDIA GPUs in Julia is provided by the CUDA.jl package. It is built on the CUDA toolkit and aims to be as full-featured and offer the same performance as CUDA C. The toolchain is mature, has been under development since 2014, and can easily be installed on any current version of Julia using the integrated package manager. -
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CuArrays.jl
A Curious Cumulation of CUDA Cuisine
CuArrays provides a fully-functional GPU array, which can give significant speedups over normal arrays without code changes. CuArrays are implemented fully in Julia, making the implementation elegant and extremely generic. -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can... -
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Poli
An easy-to-use BI server built for SQL lovers. Power data analysis
An easy-to-use BI server built for SQL lovers. Power data analysis in SQL and gain faster business insights. Platform independent web application. Single JAR file + Single SQLite DB file. Get up and running in 5 minutes. PostgreSQL, Oracle, SQL Server, MySQL, Elasticsearch... You name it. No ETLs, no generated SQL, polish your own SQL query to transform data. Pixel-perfect positioning + Drag'n'Drop support to customize the reports and charts in your own way. Utilize the power of dynamic SQL... -
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HMMBase.jl
Hidden Markov Models for Julia
HMMBase is not maintained anymore. It will keep being available as a Julia package but we encourage existing and new users to migrate to HiddenMarkovModels.jl which offers a similar interface. For more information see HiddenMarkovModels.jl: when did HMMs get so fast?. HMMBase provides a lightweight and efficient abstraction for hidden Markov models in Julia. Most HMMs libraries only support discrete (e.g. categorical) or Normal distributions. In contrast HMMBase builds upon Distributions.jl... -
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Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.