Metadata-Version: 1.0
Name: nnkit
Version: 1.4.1
Summary: NNKit: A Python framework for creating dynamic neural networks.
Home-page: http://github.com/saldavonschwartz/nnkit.git
Author: Federico Saldarini
Author-email: fede@0xfede.io
License: MIT
Description: NNKit: A Python framework for creating dynamic neural networks
        ==============================================================
        
        NNKit is a framework for creating and training neural network models, based on dynamic computation graphs.
        See `this post <https://0xfede.io/2018/05/18/nnkit.html>`_ for more info on how the framework works.
        
        Dependencies:
        =============
        - `numpy <http://www.numpy.org>`_.
        
        Installation:
        =============
        You can `pip install nnkit`, in which case Numpy will also be installed.
        Otherwise you can download the source and manually install numpy if necessary.
        
        
        Modules:
        ========
        
        The following is a list of modules, nodes and optimizers, along with the framework
        version in which they were added.
        
        
        activation:
        -----------
        * ReLU (1.0)
        * LReLU (1.0)
        * Sigmoid (1.0)
        * Tanh (1.0)
        * Softmax (1.0)
        
        arithmetic:
        -----------
        * Multiply (1.0)
        * Add (1.0)
        
        loss:
        -----
        * L1 (1.0)
        * L2 (1.0)
        * Cross Entropy (1.0)
        * Huber (1.4.0)
        
        normalization:
        --------------
        * Batch Normalization (1.0)
        
        regularization:
        ---------------
        * L2 (1.0)
        * Dropout (1.0)
        
        optimization:
        -------------
        * Gradient descent / momentum (1.0)
        * Adam / RMSProp (1.0)
        
Keywords: neural networks ai AI
Platform: UNKNOWN
