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The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

In-Person Training
Explore the AWS machine learning platform using Amazon SageMaker

Wenming Ye (Amazon Web Services), Miro Enev (NVIDIA)
Tuesday, August 21 & Wednesday, August 22
9:00am - 5:00pm
2-Day Training Location: Concourse E Level: Intermediate
Average rating: **...
(2.00, 1 rating)

Participants should plan to attend training courses on both Tuesday and Wednesday. To attend, you must register for a Platinum pass; does not include access to tutorials on Wednesday.

Wenming Ye and Miro Enev offer an overview of deep learning along with hands-on Jupyter labs, demos, and instruction. You'll learn how DL is applied in modern business practice and how to leverage building blocks from the Amazon ML family of AI services.

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

  • Learn how to rapidly build and deploy machine learning applications on the AWS platform

This training is for you because...

  • You're a program manager, developer, or data scientist.

Prerequisites:

  • A working knowledge of Python
  • A basic understanding of deep learning

Hardware and/or installation requirements:

  • A laptop

Machine learning (ML) and deep learning (DL) projects are 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 offer an overview of deep learning along with hands-on Jupyter labs, demos, and instruction. They begin by exploring the trends powering AI/DL adoption and the basics of algorithmic learning in neural networks. Wenming and Miro then dive into how DL is applied in modern business practice and demonstrate how to leverage building blocks from the Amazon ML family of AI services.

Outline

Day 1

  • Trends and motivation for deep learning (DL)

  • Basics of neural learning and common DL architectures (CNN and AE)

  • Understanding a DL project workflow

  • Introduction to Amazon ML services:

    • SageMaker, Rekognition (Image and Video), Lex, Comprehend, Translate, Transcribe, and Polly

  • Hands-on exercise: Build and run your first deep learning model on an Amazon EC2 GPU instance with the Jupyter Notebook

  • Hands-on exercise: Introduction to deep learning and SageMaker (a Jupyter-based service)

  • Hands-on exercise: Anomaly detection using auto-encoders

Day 2

  • Demo: Greengrass ML inference edge models

  • Hands-on exercise: Introduction to visual search

  • Architecture group discussion (edge-to-cloud AI, retail, etc.)

  • Hands-on exercise: Time series prediction using recurrent neural networks

  • Introduction to reinforcement learning

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
Photo of Miro Enev

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.

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Comments

lenin christ |
05/12/2018 2:36am EDT

Very impressive blog thanks for this update. keep on blogging, we are excepting these types of news only thanks.
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