Search Results for "data processing"
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Showing 16 open source projects for "data processing"
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eloomi combines Learning Management (LMS), Onboarding, Authoring, and continuous Performance Management tools in a cloud-based solution. It allows companies to optimize skill training, onboarding and employee development with strong user experience to enhance productivity and employee satisfaction. As a white label solution, the platform can be customized to mirror a company's branding and logo.
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IndexedTables.jl
Flexible tables with ordered indices
IndexedTables provides tabular data structures where some of the columns form a sorted index. It provides the backend to JuliaDB, but can be used on its own for efficient in-memory data processing and analytics. -
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DSP.jl
Filter design, periodograms, window functions
DSP.jl provides a number of common digital signal processing routines in Julia. -
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101-0250-00
ETH course - Solving PDEs in parallel on GPUs
This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering. -
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Mousetrap.jl
Finally, a GUI Engine made for Julia
Mousetrap is a GUI library designed for Julia. It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies. -
Track leads, jobs, and tasks from one easy to use software. You can access your information wherever you are, get everyone on the same page, and grow your business.
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ClimateTools.jl
Climate science package for Julia
Climate analysis tools in Julia. ClimateTools.jl is a collection of commonly-used tools in Climate science. Basics of climate field analysis are covered, with some forays into exploratory techniques associated with climate scenario design. The package is aimed to ease the typical steps of analysis of climate models outputs and gridded datasets (support for weather stations is a work-in-progress). Climate indices and bias correction functions are coded to leverage the use of multiple threads.... -
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Transducers.jl
Efficient transducers for Julia
Transducers are transformations of "sequence" of input that can be composed very efficiently. The interface used by transducers naturally describes a wide range of processes that is expressible as a succession of steps. Furthermore, transducers can be defined without specifying the details of the input and output (collections, streams, channels, etc.) and therefore achieves a full reusability. Transducers are introduced by Rich Hickey, the creator of the Clojure language. His Strange Loop... -
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FileTrees.jl
Parallel file processing made easy
Easy everyday parallelism with a file tree abstraction. Read a directory structure as a Julia data structure, (lazy-)load the files, apply map and reduce operations on the data while not exceeding available memory if possible. Make up a file tree in memory, create some data to go with each file (in parallel), write the tree to disk (in parallel). FileTrees is a set of tools to lazy-load, process and save file trees. Built-in parallelism allows you to max out all threads and processes that Julia... -
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MLDatasets.jl
Utility package for accessing common Machine Learning datasets
This package represents a community effort to provide a common interface for accessing common Machine Learning (ML) datasets. In contrast to other data-related Julia packages, the focus of MLDatasets.jl is specifically on downloading, unpacking, and accessing benchmark datasets. Functionality for the purpose of data processing or visualization is only provided to a degree that is special to some datasets. -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded... -
BrightGauge, a ConnectWise solution, was started in 2011 to fill a missing need in the small-to-medium IT Services industry: a better way to manage data and provide the value of work to clients. BrightGauge Software allows you to display all of your important business metrics in one place through the use of gauges, dashboards, and client reports. Used by more than 1,800 companies worldwide, BrightGauge integrates with popular business solutions on the market, like ConnectWise, Continuum, Webroot, QuickBooks, Datto, IT Glue, Zendesk, Harvest, Smileback, and so many more. Dig deeper into your data by adding, subtracting, multiplying, and dividing one metric against another. BrightGauge automatically computes these formulas for you. Want to show your prospects how quick you are to respond to tickets? Show off your data with embeddable gauges on public sites.
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
... implement new FE spaces, new reference elements, use external mesh generators, linear solvers, post-processing tools, etc. See, e.g., the list of available Gridap plugins. -
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AutoMLPipeline.jl
Package that makes it trivial to create and evaluate machine learning
... (Independent Component Analysis) and pca (Principal Component Analysis) transformations, respectively, concatenated with the hot-bit encoding (ohe) of categorical features (catf) of a given data for rf (Random Forest) modeling. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more... -
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Flux3D.jl
3D computer vision library in Julia
Flux3D.jl is a 3D vision library, written completely in Julia. This package utilizes Flux.jl and Zygote.jl as its building blocks for training 3D vision models and for supporting differentiation. This package also have support of CUDA GPU acceleration with CUDA.jl. -
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MLDataUtils.jl
Utility package for generating, loading, and processing ML datasets
This package is designed to be the end-user facing front-end to all the data related functionality that is spread out across the JuliaML ecosystem. Most of the following sub-categories are covered by a single back-end package that is specialized on that specific problem. Consequently, if one of the following topics is of special interest to you, make sure to check out the corresponding documentation of that package. -
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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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JuliaFEM.jl
The JuliaFEM software library is a framework
The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed...
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