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Showing 4 open source projects for "python tools"
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Out-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
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The only software you need to increase cash flow, optimize resource utilization, and take control of your assets and inventory.
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing... -
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ScikitLearn.jl
Julia implementation of the scikit-learn API
The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework. -
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InteractiveViz.jl
Interactive visualization tools for Julia
Julia already has a rich set of plotting tools in the form of the Plots and Makie ecosystems, and various backends for these. So why another plotting package? InteractiveViz is not a replacement for Plots or Makie, but rather a graphics pipeline system developed on top of Makie. It has a few objectives. To provide a simple API to visualize large or possibly infinite datasets (tens of millions of data points) easily. To enable interactivity, and be responsive even with large amounts of data... -
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CounterfactualExplanations.jl
A package for Counterfactual Explanations and Algorithmic Recourse
CounterfactualExplanations.jl is a package for generating Counterfactual Explanations (CE) and Algorithmic Recourse (AR) for black-box algorithms. Both CE and AR are related tools for explainable artificial intelligence (XAI). While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs. -
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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