eli5
Predictive model debugger
A Python package for debugging and explaining predictions of machine learning classifiers
A library for debugging/inspecting machine learning classifiers and explaining their predictions
265 stars
4 watching
43 forks
Language: Jupyter Notebook
last commit: about 1 month ago
Linked from 1 awesome list
kelvins/awesome-mlopsRelated projects:
| Repository | Description | Stars |
|---|---|---|
 dask/dask-ml | A Python library for scalable machine learning using Dask alongside popular ML libraries | 907 |
 ionelmc/python-manhole | A tool for interactive debugging of Python applications | 372 |
 locuslab/e2e-model-learning | Develops an approach to learning probabilistic models in stochastic optimization problems | 201 |
 microprediction/timemachines | Provides a simple and unified interface to various univariate time-series prediction algorithms | 413 |
 rmarko/explainprediction | An R package for explaining the predictions made by machine learning models in data science applications. | 2 |
 mi2datalab/pybreakdown | A Python implementation of a method to explain the predictions of machine learning models | 42 |
 ericjang/tdb | A tool for interactive debugging and visualization of deep learning models during training | 1,354 |
 packtpublishing/machine-learning-for-streaming-data-with-python | A comprehensive guide to building machine learning models for streaming data in Python | 68 |
 uber/manifold | An interactive tool to help machine learning practitioners visualize and debug their models' performance by comparing predictions to ground truth data. | 1,651 |
 gmonce/scikit-learn-book | Source code and data for a machine learning book with Python tutorials | 393 |
 interpretml/dice | Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding. | 1,373 |
 mlcommons/inference | Measures the performance of deep learning models in various deployment scenarios. | 1,256 |
 google/edward2 | A tool for writing probabilistic models and manipulating their computation | 680 |
 sergioburdisso/pyss3 | A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
 andosa/treeinterpreter | Provides a way to decompose scikit-learn model predictions into bias and feature contribution components. | 745 |