Put AI to Work
April 15-18, 2019
New York, NY

In-Person Training
Put deep learning to work: A practical introduction using Amazon Web Services

Wenming Ye (Amazon Web Services), Miro Enev (NVIDIA)
Monday, April 15 & Tuesday, April 16,
9:00am - 5:00pm
Location: Sutton Center

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Machine learning (ML) and deep learning (DL) projects are becoming increasingly common at enterprises and startups alike and have been a key innovation engine for Amazon businesses such as Go, Alexa, and Robotics. Wenming Ye and Miro Enev give you a practical introduction to the next step in DL learning, with lecture, demos, and hands-on labs.

What you'll learn, and how you can apply it

  • Learn how to get started with deep Learning, TensorFlow, PyTorch, and MXNet
  • Explore key trends and business scenarios in AI/DL adoption
  • Discover how to bring your models to production faster, with much less effort, at a lower cost

This training is for you because...

  • You're a practicing or aspiring ML developer or data scientist.

Prerequisites:

  • A working knowledge of Python

Machine learning (ML) and deep learning (DL) projects are becoming increasingly common at enterprises and startups alike and have been a key innovation engine for Amazon businesses such as Go, Alexa, and Robotics.

Wenming Ye and Miro Enev give you a practical introduction to the next step in DL learning, with lecture, demos, and hands-on labs. 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 learn how to leverage building blocks from the Amazon ML family of AI services, from powerful new GPU instances and convenient Amazon SageMaker built-in algorithms to ready-to-use managed AI services.

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

About your instructors

Photo of Wenming Ye

Wenming Ye is an AI/ML solutions architect at Amazon Web Services, helping researchers and enterprise customers to use cloud-based machine learning services to rapidly scale their innovations. Previously, Wenming had a diverse R&D experience at Microsoft Research, SQL engineering team, and successful startups.

Twitter for wenmingye

Miro Enev is a senior solutions architect at NVIDIA, specializing in advancing data science and machine intelligence while respecting human values. He supports the Pacific Northwest teams engaged with cloud, industrial, and retail clients while participating in research in deep reinforcement learning and edge-to-cloud AI. Miro holds a PhD from the University of Washington’s computer science and engineering department, where his thesis was on machine learning applications for information privacy in emerging sensor contexts. He studied cognitive science and computer science as an undergraduate at the University of California, Berkeley.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.