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Results 101 - 110 of 549 for host:mxnet.apache.org (0.03 sec)

  1. RowSparseNDArray - NDArray for Sparse Gradient ...

    RowSparseNDArray - NDArray for Sparse Gradient Updates Motivation Many real world datasets deal with high dimensional...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/legacy/ndarray/sparse/row_spa...
    Registered: Mon Nov 03 11:12:59 UTC 2025
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  2. Parameter and Block Naming — Apache MXNet docum...

    Parameter and Block Naming In gluon, each Parameter or Block has a name. Parameter names and Block names can be autom...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/blocks/naming.html
    Registered: Mon Nov 03 11:13:24 UTC 2025
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  3. Trainer — Apache MXNet documentation

    Trainer Training a neural network model consists of iteratively performing three simple steps. The first step is the ...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/training/trainer.html
    Registered: Mon Nov 03 11:14:33 UTC 2025
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  4. Image Augmentation — Apache MXNet documentation

    Image Augmentation Augmentation is the process of randomly adjusting the dataset samples used for training. As a resu...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/data/data_augmentation....
    Registered: Mon Nov 03 11:14:15 UTC 2025
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  5. Custom Layers — Apache MXNet documentation

    Custom Layers While Gluon API for Apache MxNet comes with a decent number of pre-defined layers , at some point one m...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/blocks/custom-layer.html
    Registered: Mon Nov 03 11:15:00 UTC 2025
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  6. Activation Blocks — Apache MXNet documentation

    Activation Blocks Deep neural networks are a way to express a nonlinear function with lots of parameters from input d...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/blocks/activations/acti...
    Registered: Mon Nov 03 11:15:22 UTC 2025
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  7. Kullback-Leibler (KL) Divergence — Apache MXNet...

    Kullback-Leibler (KL) Divergence Kullback-Leibler (KL) Divergence is a measure of how one probability distribution is...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/loss/kl_divergence.html
    Registered: Mon Nov 03 11:16:37 UTC 2025
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  8. Training — Apache MXNet documentation

    Training MXNet Gluon Fit API Trainer Learning Rates Normalization Blocks Did this page help you? Yes No Thanks for yo...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/gluon/training/index.html
    Registered: Mon Nov 03 11:16:58 UTC 2025
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  9. Moving to MXNet from Other Frameworks — Apache ...

    Moving to MXNet from Other Frameworks Comparison Guides PyTorch to MXNet (MNIST) pytorch.html This guide compares PyT...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/getting-started/to-mxnet/index.html
    Registered: Mon Nov 03 11:15:46 UTC 2025
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  10. Differences between NP on MXNet and NumPy — Apa...

    Differences between NP on MXNet and NumPy This topic lists known differences between mxnet.np and numpy . With this q...
    mxnet.apache.org/versions/master/api/python/docs/tutorials/packages/np/np-vs-numpy.html
    Registered: Mon Nov 03 11:18:26 UTC 2025
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