mummify makes model prototyping faster. The package automagically takes care of git and logging for your machine learning project so that you can focus on what's important.
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mummify is a version control tool for machine learning. It's simple, fast, and designed for model prototyping.
Add mummify.log(<string>) to the bottom of a machine learning model:
from sklearn.datasets import load_wine
from sklearn.neighbors import KNeighborsClassifier
import mummify
data = load_wine()
X, y = data.data, data.target
model = KNeighborsClassifier(n_neighbors=4)
model.fit(X, y)
accuracy = round(model.score(X, y), 4)
mummify.log(f'Accuracy: {accuracy}')
Run the model at the command line:
python model.py
Edit the model to implement another algorithm:
...
model = LogisticRegression()
model.fit(X, y)
accuracy = round(model.score(X, y), 4)
mummify.log(f'Accuracy: {accuracy}')
Inspect model history at the command line with:
mummify history
And peek at the logged messages at the command line with:
cat mummify.log
Switch to an earlier version of the model:
mummify switch <id>
mummify will persist snapshots and the mummify.log file between switches.
pip install mummify
For feature requests or bug reports, please use Github Issues
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