Showing 5 open source projects for "python neural network"

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    Empact Foundation Class Library

    Cross-platform C++ library for use as a default application framework.

    ...Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework.
    Downloads: 12 This Week
    Last Update:
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  • 2
    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ResNeXt is a deep neural network architecture for image classification built on the idea of aggregated residual transformations. Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive parameter blowup. ...
    Downloads: 0 This Week
    Last Update:
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  • 3
    PyGObject for Windows

    PyGObject for Windows

    All-In-One PyGI/PyGObject for Windows Installer

    Cross-platform python dynamic bindings of GObject-based libraries for Windows 32-bit and 64-bit.
    Downloads: 24 This Week
    Last Update:
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  • 4
    char-rnn

    char-rnn

    Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)

    char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. ...
    Downloads: 0 This Week
    Last Update:
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  • 5

    neuranep

    Neural Network Engineering Platform

    ...SpikeOS was oriented towards computational modeling. NeuraNEP is oriented toward neural network research.
    Downloads: 0 This Week
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