October 28–31, 2019

2-Day Training Courses

All training courses take place 9:00am–5:00pm, Monday, October 28–Tuesday, October 29. In order to maintain a high level of hands-on learning and instructor interaction, each training course is limited in size.

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.

Monday, October 28 - Tuesday, October 29

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9:00am - 5:00pm Monday, October 28 & Tuesday, October 29
Location: Great America Meeting Room 3
Shashank Prasanna (Amazon Web Services), Vikrant Kahlir (Amazon Web Services), Rama Thamman (Amazon Web Services)
Amazon Web Services (AWS) offers a breadth and depth of services to easily build, train, and deploy TensorFlow models. Shashank Prasanna, Vikrant Kahlir, and Rama Thamman give you hands-on experience working with these services. Read more.
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9:00am - 5:00pm Monday, October 28 & Tuesday, October 29
Location: Room 204
Robert Schroll (The Data Incubator)
The TensorFlow library provides for the use of computational graphs with automatic parallelization across resources, ideal architecture for implementing neural networks. Robert Schroll introduces TensorFlow's capabilities in Python, moving from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications. Read more.
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9:00am - 5:00pm Monday, October 28 & Tuesday, October 29
Location: Room 212
Maxim Lukiyanov (Microsoft), Vaidyaraman Sambasivam (Microsoft), Mehrnoosh Sameki (MERS) (Microsoft), Santhosh Pillai (Microsoft)
Maxim Lukiyanov, Vaidyaraman Sambasivam, Mehrnoosh Samekihow, and Santhosh Pillai explore how AzureML helps data scientists be more productive when working through developing TensorFlow models for production. You'll see the whole model development lifecycle from training through deployment, ML ops, and all the way to model interpretability. Read more.
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9:00am - 5:00pm Monday, October 28 & Tuesday, October 29
Location: Room 211
Valliappa Lakshmanan shows you how to use Google Cloud Platform to design and build machine learning (ML) models and how to deploy them into production. You'll walk through the process of building a complete machine learning pipeline from ingest and exploration to training, evaluation, deployment, and prediction. Read more.
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9:00am - 5:00pm Monday, October 28 & Tuesday, October 29
Location: Room 203
Aurélien Géron (Kiwisoft)
Aurélien Géron dives into creating production ML pipelines with TensorFlow Extended (TFX) and using TFX to move from ML coding to ML engineering. You'll walk through the basics and put your first pipeline together, then learn how to customize TFX components and perform deep analysis of model performance. Read more.

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