Metadata-Version: 1.1
Name: Hebel
Version: 0.02.1
Summary: GPU-Accelerated Deep Learning Library in Python
Home-page: https://github.com/hannes-brt/hebel
Author: Hannes Bretschneider
Author-email: hannes@psi.utoronto.ca
License: GPLv2
Description: Hebel
        =====
        
        GPU-Accelerated Deep Learning Library in Python
        
        Hebel is a library for deep learning with neural networks in Python
        using GPU acceleration with CUDA through PyCUDA. It implements the most
        important types of neural network models and offers a variety of
        different activation functions and training methods such as momentum,
        Nesterov momentum, dropout, and early stopping.
        
        Models
        ------
        
        Right now, Hebel implements feed-forward neural networks for
        classification and regression on one or multiple tasks. Other models
        such as Autoencoder, Convolutional neural nets, and Restricted Boltzman
        machines are planned for the future.
        
        Hebel implements dropout as well as L1 and L2 weight decay for
        regularization.
        
        Optimization
        ------------
        
        Hebel implements stochastic gradient descent (SGD) with regular and
        Nesterov momentum.
        
        Compatibility
        -------------
        
        Currently, Hebel will run on Linux and Windows, and probably Mac OS X
        (not tested).
        
        Dependencies
        ------------
        
        -  PyCUDA
        -  numpy
        -  PyYAML
        -  skdata (only for MNIST example)
        
        Installation
        ------------
        
        Hebel is on PyPi, so you can install it with
        
        ::
        
            pip install hebel
        
        Getting started
        ---------------
        
        Study the yaml configuration files in ``examples/`` and run
        
        ::
        
            python train_model.py examples/mnist_neural_net_shallow.yml
        
        The script will create a directory in ``examples/mnist`` where the
        models and logs are saved.
        
        Read the Getting started guide at
        `hebel.readthedocs.org/en/latest/getting\_started.html <http://hebel.readthedocs.org/en/latest/getting_started.html>`__
        for more information.
        
        Documentation
        -------------
        
        `hebel.readthedocs.org <http://hebel.readthedocs.org>`__ (coming slowly)
        
        Contact
        -------
        
        Maintained by `Hannes Bretschneider <http://github.com/hannes-brt>`__
        (hannes@psi.utoronto.ca). If your are using Hebel, please let me know
        whether you find it useful and file a Github issue if you find any bugs
        or have feature requests.
        
        What's with the name?
        ---------------------
        
        *Hebel* is the German word for *lever*, one of the oldest tools that
        humans use. As Archimedes said it: *"Give me a lever long enough and a
        fulcrum on which to place it, and I shall move the world."*
        
Keywords: cuda gpu machine-learning deep-learning neural-networks
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
