Metadata-Version: 2.1
Name: pandas-ml-utils-torch
Version: 0.2.0
Summary: Augment pandas DataFrame with methods for machine learning
Home-page: https://github.com/KIC/pandas-ml-quant
Author: KIC
Author-email: 
License: MIT
Description: # pytorch extension for [pandas-ml-utils][ghl1]
        
        Adds a `PytorchModel` to the pandas ml utils suite. While a regular class extending `nn.Module` is sufficient,
        there is also a special class `PytorchNN` which can be extended as well. Using this class has the following 
        advantages:
        
         * allows to use L1, L2 regularisation -> [example][ghl2] 
         * allows different forward path for training and prediction (useful i.e. for re-parametrisation trick) -> [example][ghl3]
         * allows to implement auto-encoders easily by just providing the encode/decode functions
         * added loss functions like SoftDTW (fit Timeseries) loss or HeteroscedasticityLoss (fit Normal Distribution) -> [example][ghl3]
        
        <br><br>
        
        ![Fitting Example][ghi1]
        
        [ghl1]: ../pandas-ml-utils
        [ghl2]: ./examples/regression_with_regularization.ipynb
        [ghl3]: ./examples/probabilistic_model.ipynb
        [ghi1]: ../.readme/videos/probabilistic-model-fit.gif
        
        
Keywords: pandas,ml,util,quant
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
