roywei commented on a change in pull request #13411: [WIP] Gluon end to end tutorial URL: https://github.com/apache/incubator-mxnet/pull/13411#discussion_r246210913
########## File path: docs/tutorials/gluon/gluon_from_experiment_to_deployment.md ########## @@ -0,0 +1,489 @@ + +# Gluon: from experiment to deployment, an end to end example + +## Overview +MXNet Gluon API comes with a lot of great features and it can provide you everything you need from experiment to deploy the model. In this tutorial, we will walk you through a common use case on how to build a model using gluon, train it on your data, and deploy it for inference. + +Let's say you need to build a service that provides flower species recognition. A common use case is, you don't have enough data to train a good model. In such cases we use a technique called Transfer Learning. +In Transfer Learning we make use of a pre-trained model that solves a related task but is trained on a very large standard dataset such as ImageNet from a different domain, we utilize the knowledge in this pre-trained model to perform a new task at hand. + +Gluon provides State of the Art models for many of the standard tasks such as Classification, Object Detection, Segmentation, etc. In this tutorial we will use the pre-trained model [ResNet50 V2](https://arxiv.org/abs/1603.05027) trained on ImageNet dataset, this model achieves 77.11% top-1 accuracy on ImageNet, we seek to transfer as much knowledge as possible for our task of recognizing different species of Flowers. + +In this tutorial we will show you the steps to load pre-trained model from Gluon, tweak the model according to your need, fine-tune the model on your small dataset, and finally deploy the trained model to integrate with your service. + + + + +## Prerequisites + +To complete this tutorial, you need: + +- [Build MXNet from source](https://mxnet.incubator.apache.org/install/ubuntu_setup.html#build-mxnet-from-source) with Python(Gluon) and C++ Packages +- Learn the basics about Gluon with [A 60-minute Gluon Crash Course](https://gluon-crash-course.mxnet.io/) +- Learn the basics about [MXNet C++ API](https://github.com/apache/incubator-mxnet/tree/master/cpp-package) + + +## The Data + +We will use the [Oxford 102 Category Flower Dateset](http://www.robots.ox.ac.uk/~vgg/data/flowers/102/) as an example to show you the steps. You can use this [script](https://github.com/Arsey/keras-transfer-learning-for-oxford102/blob/master/bootstrap.py) to download and organize your data into train, test, and validation sets. Simply import it and run: Review comment: Forgot to updated the instruction, this script is already added in tutorial_utils, so just run the code block in the notebook will suffice. No download needed, updated instruction now. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
