Metadata-Version: 2.1
Name: neptune-fastai
Version: 0.9.2
Summary: Neptune.ai fast.ai integration library
Home-page: https://neptune.ai/
Author: neptune.ai
Author-email: contact@neptune.ai
License: Apache License 2.0
Project-URL: Tracker, https://github.com/neptune-ai/neptune-fastai/issues
Project-URL: Source, https://github.com/neptune-ai/neptune-fastai
Project-URL: Documentation, https://docs.neptune.ai/integrations-and-supported-tools/model-training/fastai
Description: # Neptune - fast.ai integration
        
        See [the official docs](https://docs.neptune.ai/integrations-and-supported-tools/model-training/fastai).
        
        ```python
        from fastai.basics import URLs, untar_data, accuracy
        from fastai.tabular.all import tabular_learner, TabularDataLoaders, Categorify, FillMissing, Normalize
        from fastai.callback.all import SaveModelCallback
        
        from neptune import new as neptune
        from neptune_fastai.impl import NeptuneCallback
        
        
        neptune_run = neptune.init()
        
        path = untar_data(URLs.ADULT_SAMPLE)
        
        dls = TabularDataLoaders.from_csv(path / 'adult.csv',
                                          path=path,
                                          y_names="salary",
                                          cat_names=[
                                              'workclass',
                                              'education',
                                              'marital-status',
                                              'occupation',
                                              'relationship',
                                              'race'
                                          ],
                                          cont_names=['age', 'fnlwgt', 'education-num'],
                                          procs=[Categorify, FillMissing, Normalize])
        
        learn = tabular_learner(dls,
                                metrics=accuracy)
        learn.fit_one_cycle(10,
                            cbs=[
                                    NeptuneCallback(run=neptune_run,
                                                    base_namespace='experiment',
                                                    save_best_model=True,
                                                    save_model_freq=4),
                                    SaveModelCallback(monitor='accuracy', every_epoch=True)
                                ])
        ```
Keywords: MLOps,ML Experiment Tracking,ML Model Registry,ML Model Store,ML Metadata Store
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
Provides-Extra: all
Provides-Extra: dev
