DrWhy
ML framework
A collection of tools and guidelines for building responsible machine learning models
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
682 stars
35 watching
85 forks
Language: R
last commit: over 3 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 h2oai/article-information-2019 | A framework for building and evaluating machine learning systems with high accuracy and interpretability, particularly in human-centered applications. | 13 |
 mlr-org/mlr | Provides an infrastructure for machine learning in R, enabling users to focus on experiments without writing lengthy wrappers and boilerplate code. | 1,648 |
| modeloriented/modelstudio | A tool for creating interactive, model-agnostic explanations of machine learning models in R | 328 |
 mlreef/mlreef | A platform for collaboration, data management, and reproducibility in machine learning development | 1,440 |
 a3data/hermione | A framework for simplifying machine learning development and deployment | 207 |
 jhashanti/machine-learning-with-r | A comprehensive R package providing tools and techniques for building machine learning models in supervised learning. | 9 |
| modeloriented/dalex | A tool to help understand and explain the behavior of complex machine learning models | 1,390 |
 microsoft/0xdeca10b | A framework for hosting and training machine learning models on a blockchain, enabling secure sharing and prediction without requiring users to pay for data or model updates. | 559 |
| modeloriented/ibreakdown | A tool for explaining predictions from machine learning models by attributing them to specific input variables and their interactions. | 82 |
| h2oai/mli-resources | Provides tools and techniques for interpreting machine learning models | 483 |
 sethjuarez/numl | Provides a set of reusable C# components for building machine learning models in .NET | 431 |
| mlr-org/mlr3 | Provides an object-oriented framework for efficient machine learning in R | 952 |
 asappresearch/flambe | An ML framework for accelerating research and its integration into production workflows | 264 |
 leopiney/tensor-safe | A Haskell framework for defining and compiling valid deep learning models to external frameworks like TensorFlow JS or Keras. | 101 |
 somnibyte/mlkit | A framework for implementing machine learning algorithms in Swift to make it easier for developers to incorporate ML into their projects. | 152 |