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
Amazon Web Services (AWS) offers a breadth and depth of services to easily build, train, and deploy TensorFlow models. In this 2-day training session, get 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 209
Rich Ott (The Data Incubator)
This course is a non-technical overview of AI and data science. You’ll learn common techniques, how to apply them in your organization, and common pitfalls to avoid. Though this course, you’ll pick up the language and develop a framework to be able to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making. 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. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move 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 203
Maxim Lukiyanov (Microsoft), Aashish Bhateja (Microsoft), Jordan Edwards (Microsoft ), Mehrnoosh Sameki (MERS) (Microsoft)
In this 2-day training, we will show how AzureML helps the data scientist to be more productive when working through the process of developing TensorFlow models for production. We will show participants aspects across the whole model development lifecycle from training, through deployment, MLOps, 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 212
An introduction to designing and building machine learning models on Google Cloud Platform, and how to deploy them into production. We'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 211
Sign up for this 2-day training on creating production ML pipelines using TensorFlow Extended (TFX) and learn how you can use TFX to move from ML coding to ML engineering! We'll be covering the basics and walking you through putting your first pipeline together, and then we'll go deeper and learn how to customize TFX components and perform deep analysis of model performance. Read more.

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Contact list

View a complete list of TensorFlow World Conference contacts