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SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. ... -
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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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ClimateMachine.jl
Earth System Model that automatically learns from data
...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 extremes, and high-impact storms. -
Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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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. ... -
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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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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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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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DISTOD
Distributed discovery of bidirectional order dependencies
The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. -
Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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InfoPoint
A flexible data management system
InfoPoint is a flexible data management system, intended not only to store data itself but also to provide interfaces to other sources or targets of comparable structured data. -
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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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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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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 different layouts and formats (pdf, HTML, presentation slides, etc). -
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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 already exists in your registry, this Action attempts to pull that image as a cache to reduce uncessary build steps. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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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 learnable weights and biases. ... -
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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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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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QuiclickRNAseq
An integrated pipeline for RNA-seq analysis
Quiclick is a python framework for RNA-seq data analysis, including data trimming, mapping, counting and RNA editing analysis. -
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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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StellarGraph
Machine Learning on Graphs
...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 contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. ... -
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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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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. ...
