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 http://www.apache.org/licenses/LICENSE-2.0

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Gluon

Getting started

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.. card:: :title: A 60-minute Gluon crash course :link: ../../getting-started/crash-course/index.html

  Six 10-minute tutorials covering the core concepts of MXNet using the Gluon API.

.. card:: :title: Gluon - Neural network building blocks :link: blocks/nn.html

  An introduction to defining and training neural networks with Gluon.

.. card:: :title: Gluon: from experiment to deployment :link: ../../getting-started/gluon_from_experiment_to_deployment.html

  An end to end tutorial on working with the MXNet Gluon API.

.. card:: :title: Custom Layers for Beginners :link: blocks/custom_layer_beginners.html

  A guide to implementing custom layers for beginners.

.. card:: :title: Logistic regression using Gluon API explained :link: ../../getting-started/logistic_regression_explained.html

  Implementing logistic regression using the Gluon API.

.. card:: :title: Saving and Loading Gluon Models :link: blocks/save_load_params.html

  Saving and loading trained models.

Data

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.. card:: :title: Data Augmentation :link: data/data_augmentation.html

  Boost your training dataset with image augmentation.

.. card:: :title: Gluon Datasets and DataLoader :link: data/datasets.html

  A guide to loading data using the Gluon API.

Training

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.. card:: :title: Neural Networks :link: blocks/nn.html

  How to use Layers and Blocks.

.. card:: :title: Normalization Blocks :link: training/normalization/index.html

  Understand usage of normalization layers (such as BatchNorm).

.. card:: :title: Activation Blocks :link: blocks/activations/activations.html

  Understand usage of activation layers (such as ReLU).

.. card:: :title: Loss Functions :link: loss/loss.html

  How to use loss functions for predicting outputs.

.. card:: :title: Initializing Parameters :link: blocks/init.html

  How to use the init function.

.. card:: :title: Parameter Management :link: blocks/parameters.html

  How to manage parameters.

.. card:: :title: Fit API Tutorial :link: training/fit_api_tutorial.html

  How to use the fit API

.. card:: :title: Learning Rate Finder :link: training/learning_rates/learning_rate_finder.html

  How to use the Learning Rate Finder to find a good learning rate.

.. card:: :title: Learning Rate Schedules :link: training/learning_rates/learning_rate_schedules.html

  How to schedule Learning Rate change over time.

.. card:: :title: Trainer :link: training/trainer.html

  How to update neural network parameters using an optimization method.

.. card:: :title: Autograd API :link: ../autograd/index.html

  How to use Automatic Differentiation with the Autograd API.

Advanced Topics

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.. card:: :title: Naming :link: blocks/naming.html

  Best practices for the naming of things.

.. card:: :title: Custom Layers :link: blocks/custom-layer.html

  A guide to implementing custom layers.

.. card:: :title: Custom Operators :link: ../../extend/customop.html

  Building custom operators with numpy.

.. card:: :title: Custom Loss :link: loss/custom-loss.html

  A guide to implementing custom losses.

.. card:: :title: Hybridize :link: blocks/hybridize.html

  Speed up training with hybrid networks.

.. card:: :title: Learning Rate Schedules (Advanced) :link: training/learning_rates/learning_rate_schedules_advanced.html

  How to schedule Learning Rate change over time (advanced)

Applications Topics

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.. card:: :title: Image Tutorials :link: image/index.html

  How to create deep learning models for images.

.. card:: :title: Text Tutorials :link: text/index.html

  How to create deep learning models for text.

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/index