| .. Licensed to the Apache Software Foundation (ASF) under one |
| or more contributor license agreements. See the NOTICE file |
| distributed with this work for additional information |
| regarding copyright ownership. The ASF licenses this file |
| to you under the Apache License, Version 2.0 (the |
| "License"); you may not use this file except in compliance |
| with the License. You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, |
| software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| KIND, either express or implied. See the License for the |
| specific language governing permissions and limitations |
| under the License. |
| |
| Gluon |
| ===== |
| |
| Getting started |
| --------------- |
| |
| .. container:: cards |
| |
| .. 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 |
| ---- |
| |
| .. container:: cards |
| |
| .. 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 |
| -------- |
| |
| .. container:: cards |
| |
| .. 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 |
| --------------- |
| |
| .. container:: cards |
| |
| .. 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 |
| ------------------- |
| |
| .. container:: cards |
| |
| .. 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. |
| |
| |
| .. toctree:: |
| :hidden: |
| :maxdepth: 3 |
| :glob: |
| |
| */index* |