shapeland
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| shapeland | facet | |
|---|---|---|
| 2 | 5 | |
| 96 | 471 | |
| - | - | |
| 0.0 | 5.6 | |
| about 2 years ago | 10 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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.
shapeland
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/r/technology top posts: Mar 1, 2021
FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models.\ (0 comments)
- FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models.
- Human-Explainable AI
- Facet: ML model inspection and model-based simulation for better explanations
What are some alternatives?
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
transient_rotordynamic - transient dynamics of elastic rotors in journal bearings with Julia and Python
shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
wordlescraper - Combine wordle statistics metrics from various locations, data science to correlate scores with words, and a front end to display the results.
transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).