Search Results for "qt-based"
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Showing 6 open source projects for "qt-based"
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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FAST-GHG
A fast tool to caculatate greenhouse gases in agriculture
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
...Using our tool, you can choose features, like miRNAs, with the most significant diagnostic potential (based on the results of miRNA-seq, for validation in qPCR experiments). -
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geocompr
Geocomputation with R: an open source book
This repository hosts the source for Geocomputation with R, an open-source book covering spatial data analysis, visualization, and modeling using R. It teaches how to work with vector and raster data, coordinate systems, mapping, and geocomputation techniques using packages like sf, terra, tmap, and more. Actively maintained and updated for real-world geospatial workflows. -
Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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rethinking
Statistical Rethinking course and book package
This R package accompanies Richard McElreath’s Statistical Rethinking (2nd edition), offering utilities to fit and compare Bayesian models using both MAP estimation (quap) and Hamiltonian Monte Carlo via RStan (ulam). It supports specifying models via explicit distributional assumptions, providing flexibility for advanced statistical workflows. -
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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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