yellowbrick VS explainerdashboard

Compare yellowbrick vs explainerdashboard and see what are their differences.

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yellowbrick explainerdashboard
2 2
4,198 2,228
0.3% -
2.8 7.8
9 months ago 27 days ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

yellowbrick

Posts with mentions or reviews of yellowbrick. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

explainerdashboard

Posts with mentions or reviews of explainerdashboard. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

When comparing yellowbrick and explainerdashboard you can also consider the following projects:

kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

Anaconda - Anaconda turns your Sublime Text 3 in a full featured Python development IDE including autocompletion, code linting, IDE features, autopep8 formating, McCabe complexity checker Vagrant and Docker support for Sublime Text 3 using Jedi, PyFlakes, pep8, MyPy, PyLint, pep257 and McCabe that will never freeze your Sublime Text 3

Transformer-MM-Explainability - [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

itermplot - An awesome iTerm2 backend for Matplotlib, so you can plot directly in your terminal.

WeightWatcher - The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

seaborn-image - High-level API for attractive and descriptive image visualization in Python

TorchDrift - Drift Detection for your PyTorch Models

fpdf2 - Simple PDF generation for Python

backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

scikit-survival - Survival analysis built on top of scikit-learn

delve - PyTorch model training and layer saturation monitor