Fully automated machine learning in one-liners.
Fully Automated Machine Learning in One-Liners
Libra is a deep learning API that allows users to use machine learning in their workflows in fluent one-liners. It is written in Python and TensorFlow and makes training neural networks as simple as a one line function call. It was written to make deep learning as simple as possible to every user.
Install latest release version:
pip install -U libra
Install directory from github:
git clone https://github.com/Palashio/libra.git cd libra pip install .
conda install libra -c conda-forge
Usage: the basics
The core functionality of libra works through the
client object. A new client object should be created for every dataset that you want to produce results for. All information about the models that're built, the plots that are generated, and the metrics are created will be stored in the object.
You can then call different queries on that client object, and the dataset you passed to it will be used.
from libra import client newClient = client('path/to/dataset') newClient.neural_network_query('please model the median number of households')
will return a dictionary of all the information that was generated:
dict_keys(['id', 'model', 'num_classes', 'plots', 'target', 'preprocesser', 'interpreter', 'test_data', 'losses', 'accuracy'])
Other queries can also be called on the same object, and will be appended to the
newClient.svm_query('predict the proximity to the ocean') newClient.models().keys() dict_keys(['regression_ANN', svm'])
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