MXNet/Gluon Bootcamp

Setup

Since this repository contains submodules use the following command to clone:

git clone --recurse-submodules https://github.com/cyrusmvahid/GluonBootcamp.git

Schedule

Day 1

Title	Description	Duration	Presenter
MXNet & Gluon Overview	An overview of MXNet architecture and components	30 mins	Thom
SageMaker Setup	Get configured for the day ahead	15 mins	Christian
Crash Course (LAB)	Walkthrough of core Gluon components, and use them to create and train a convolutional neural network	120 mins	Thom & Cyrus
Custom DataSets and DataLoaders	Create customized DataSets and DataLoaders for various data types	30 mins	Thom
MultiGPU Training (LAB)	An introduction to training using multiple GPUs in Gluon, and hands on lab	60 mins	Eden
Multi Host Training	A deeper dive into cluster setup, sizing, optimization algorithms, and other considerations for distributed training	60 mins	Eden & Cyrus
SageMaker Deep-Dive	A deep-dive into SageMaker SDK and security model	30 mins	Christian
SageMaker DevOps	A deep dive into how to integrate SageMaker into development pipeline for teams of data scientists	30 mins	Christian
Multi Host Training with SageMaker(LAB)	Participants learn the simple steps to training using a cluster with Gluon and Amazon Sagemaker	30 mins	Eden

Day2

Title	Description	Duration	Presenter
Deep Learning AMI Setup	An introduction to DLAMI and get configured for the day ahead	30 mins	Christian
Beyond the Defaults	Use simple regression model we take a look at alternatives for initialization, optimization and evaluation.	30 mins	Cyrus
MXBoard	Using MXNet with Tensorboard to monitor training	30 mins	Thom
GluonNLP	Walk through of key motivations and features of the GluonNLP toolkit.	30 mins	Cyrus
Stacked Bidirectional LSTM (LAB)	We work up from plain RNN to Stacked Bi-directional LSTMs using Gluon layers	60 mins	Thom
LSTM Model (LAB)	Participant in this section implement a simple LSTM network	60 mins	Cyrus
LSTNet Theory	This section describes theory of Long and Short Term Temporal Patterns with Deep Neural Networks	30 mins	Cyrus
LSTNet Implementation (LAB)	While referencing the paper, we construct the LSTNet model and train on multi-gpu	90 mins	Thom
LSTNet Multi GPU (LAB)	Scale training of LSTNet model with Multi GPU	30 mins	Cyrus

Day3

Title	Description	Duration	Presenter
Profiling MXNet	Analysis of runtime code to identify performance bottlenecks	30 mins	Thom
Moving LSTNet to SageMaker(LAB)	The LSTNet code will be ported to train on Amazon SageMaker using the Python SDK	90 mins	Eden
Distributed LSTNet on SageMaker(LAB)	Participants will speed up the training of the LSTNet model with data distribution across multiple GPUs and hosts	30 mins	Eden
SageMaker Automatic Model Tuning	A look at SageMaker's hyperparameter optimization features	60 mins	Thom
Deploying with SageMaker (LAB)	We discover three scenarios, Deploying a model developed in SageMaker, Deploying model artefacts from S3, and deploying model artefacts from docker image	60 mins	Eden
MXNet on Edge with Raspberry PI	We demonstrate a simple model that runs on Raspberry PI 3	30 min	Christian
MXNet on Edge with Amazon Greengrass	IWe demonstrate deployment of a simple CV model on Amazon GreenGrass using Lambda	30 mins	Christian
Keras-MXNet 2 (LAB)	We use Keras to implement a bi-directional LSTM using Keras and the MXNet backend	30 mins	Cyrus
GluonCV toolkit	Walk through of key features of the GluonCV toolkit, with demo.	30 mins	Thom

Day4

Title	Description	Duration	Presenter
Gluon project structure	Suggestions on how you can organize your MXNet Gluon projects.	30 mins	Cyrus
Hackathon	A project based on bi-directional LSTM will be implemented to incorporate all the material from the first three days. If participants have prepared datasets of significant size we attempt to optimize the distributed training for large batch sizes	6.5 hours	All

## Convert to markdown
# !notedown README.ipynb --to markdown > README.MD

## Convert to slides
# jupyter nbconvert <your notebook> --to slides --reveal-prefix reveal.js
## then copy the html file to `slides/note2slides` containing reveal.js