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universal-ctags
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public |
A maintained ctags implementation
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2025-10-05 |
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r-bundle
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public |
Typically, models in 'R' exist in memory and can be saved via regular 'R' serialization. However, some models store information in locations that cannot be saved using 'R' serialization alone. The goal of 'bundle' is to provide a common interface to capture this information, situate it within a portable object, and restore it for use in new settings.
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2025-10-05 |
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r-tidybins
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public |
Multiple ways to bin numeric columns with a tidy output. Wraps a variety of existing binning methods into one function, and includes a new method for binning by equal value, which is useful for sales data. Provides a function to automatically summarize the properties of the binned columns.
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2025-10-05 |
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wgpu-native
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public |
A native WebGPU implementation in Rust, based on wgpu-core.
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2025-10-05 |
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hypothesis
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public |
A library for property based testing
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2025-10-05 |
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litellm
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public |
Library to easily interface with LLM API providers
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2025-10-05 |
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rich-click
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public |
Format click help output nicely with rich
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2025-10-05 |
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grpcio
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public |
gRPC - A high-performance, open-source universal RPC framework
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2025-10-05 |
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grpcio-tools
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public |
gRPC - A high-performance, open-source universal RPC framework
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2025-10-05 |
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libgrpc
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public |
gRPC - A high-performance, open-source universal RPC framework
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2025-10-05 |
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django-mptt2
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public |
Utilities for implementing Modified Preorder Tree Traversal with your Django Models and working with trees of Model instances.
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2025-10-05 |
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django-orghierarchy
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public |
Reusable Django application for hierarchical organizations.
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2025-10-05 |
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django-plotly-wagtail
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public |
Django Wagtail use of django-plotly-dash and plotly dash
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2025-10-05 |
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django-otlp-log-exporter
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public |
integrate Django & SDK provided by OpenTelemetry and directly forward the logs from the application to OpenTelemetry.
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2025-10-05 |
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demesdraw
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public |
drawing tools for Demes demographic models
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2025-10-05 |
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stackvana
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public |
stackvana build up to lsst_distrib
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2025-10-05 |
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stackvana-lsst_distrib
|
public |
stackvana build up to lsst_distrib
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2025-10-05 |
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r-shinymodels
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public |
Launch a 'shiny' application for 'tidymodels' results. For classification or regression models, the app can be used to determine if there is lack of fit or poorly predicted points.
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2025-10-04 |
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r-finetune
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public |
The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <arXiv:1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.
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2025-10-04 |
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r-autostats
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public |
Automatically do statistical exploration. Create formulas using 'tidyselect' syntax, and then determine cross-validated model accuracy and variable contributions using 'glm' and 'xgboost'. Contains additional helper functions to create and modify formulas. Has a flagship function to quickly determine relationships between categorical and continuous variables in the data set.
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2025-10-04 |
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r-probably
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public |
Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations.
|
2025-10-04 |
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r-usemodels
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public |
Code snippets to fit models using the tidymodels framework can be easily created for a given data set.
|
2025-10-04 |
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r-stacks
|
public |
Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.
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2025-10-04 |
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casacpp
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public |
C++ libraries underlying CASA, the radio astronomical data processing package
|
2025-10-04 |
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r-workflowsets
|
public |
A workflow is a combination of a model and preprocessors (e.g, a formula, recipe, etc.) (Kuhn and Silge (2021) <https://www.tmwr.org/>). In order to try different combinations of these, an object can be created that contains many workflows. There are functions to create workflows en masse as well as training them and visualizing the results.
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2025-10-04 |
