Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

In-Person Training
Machine learning with TensorFlow

Robert Schroll (Data Incubator)
Monday, March 13 & Tuesday, March 14, 9:00am - 5:00pm
Secondary topics:  Deep learning
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Early Price ends January 20

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Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Tuesday.

Robert Schroll demonstrates TensorFlow's capabilities through its Python interface and explores TFLearn, a high-level deep learning library built on TensorFlow. Join in to learn how to use TFLearn and TensorFlow to build machine-learning models on real-world data.

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

  • Understand TensorFlow's capabilities
  • Explore TFLearn, a high-level deep learning library built on TensorFlow

Robert Schroll demonstrates TensorFlow’s capabilities through its Python interface and explores TFLearn, a high-level deep learning library built on TensorFlow. The TensorFlow library allows the use of data flow graphs for numerical computations with automatic parallelization across several CPUs or GPUs. This architecture makes it ideal for implementing neural networks and other machine-learning algorithms. Join in to learn how to use TFLearn and TensorFlow to build machine-learning models on real-world data.

About your instructor

Photo of Robert Schroll

Robert Schroll is the data scientist in residence at the Data Incubator. Previously, he held postdocs in Amherst, Massachusetts, and Santiago, Chile, where he realized that his favorite parts of his job were teaching and analyzing data. He made the switch to data science and has been at the Data Incubator since. Robert holds a PhD in physics from the University of Chicago.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package. Early Price ends January 20.

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Comments

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
01/11/2017 9:17am PST

Attendees should have a working knowledge of Python. Some familiarity with basic machine learning is helpful, but not strictly necessary. No knowledge of TensorFlow will be assumed.

Closer to the course, we’ll post some setup instructions to get you going. It will be helpful to complete those before the first day, so we can dive right in.

Young Lee | STUDENT
01/09/2017 7:47pm PST

What are the backgrounds and/or prerequisite(s) for this tutorial?