Put deep learning to work: A practical introduction using Amazon Web Services (Day 2)

Location: 114

Secondary topics: Deep Learning, Deep Learning tools, Machine Learning

Average rating:

(4.67, 3 ratings)

Who is this presentation for?

You're an aspiring ML developer, practicing ML developer, or data scientist.

Description

You’ll explore the current trends powering AI/DL adoption and algorithmic learning in neural networks, dive into how DL is applied in modern business practices, and leverage building blocks using the Amazon ML family of AI services from powerful new GPU instances to convenient Amazon SageMaker built-in algorithms to ready-to-use managed AI services.

Outline

Day 1

Deep learning and reinforcement learning trends
Neural learning and common DL architectures
Understanding a DL project workflow by example
Introduction to high-level Amazon ML Services
Amazon SageMaker (a Jupyter-based service) with Amazon Elastic Inference
Running TensorFlow and PyTorch on SageMaker

Day 2

Group discussion: Bring your own deep learning problem
SageMaker custom and built-in algorithms
Time series prediction using recurrent neural networks
Current topics in NLP
Introduction to reinforcement learning and the AWS DeepRacer

Prerequisite knowledge

A working knowledge of Python

What you'll learn

Understand deep learning, TensorFlow, PyTorch, MXNet, and key trends and business scenarios in AI/DL adoption
Learn to bring your models to production faster, with much less effort, and at lower cost