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
Average rating: **...
(2.75, 4 ratings)

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

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Comments

JUNYI ZHANG | ASSISTANT PROFESSOR
03/10/2017 7:49am PST

Thanks Robert for the info and all the preparations you’ve done for us. I have Anaconda installed with tensorflow 1.0.1. It works really nice with some tutorial examples. Can’t wait for the course. It gonna be fantastic.

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
03/09/2017 9:34am PST

Hi everyone, We’re just getting done updating our curriculum to take advantage of the recently-released TensorFlow 1.0. Rather than worry about getting everyone updated to the new version, we’ve decided to provide everyone with a cloud computer to use for the course. All you’ll need is a computer with a web browser; I’ll have the authentication details Monday morning. (And instructions on how to download copies on Tuesday afternoon.)

That said, if you want to follow along on your own computer, you’ll need at least TensorFlow 1.0 and the Jupyter notebook server. We recommend using conda to manage your Python environments, but the details are up to you.

Phillip Kriegel | SYSTEMS ENGINEER
03/09/2017 7:56am PST

When will the set up instructions be posted? Will they be posted somewhere here or will they be emailed to us?

Lucas Allen | DATA SCIENTIST
03/08/2017 10:02pm PST

Robert, will you be posting an update for what TensorFlow installation you expect?

JUNYI ZHANG | ASSISTANT PROFESSOR
02/02/2017 5:34am PST

Hope to seeing all of you soon. By the way, any Python package such as scikit-learn to begin with? Probabily a list of packages will be helpful.

Picture of Jason Perdue
Jason Perdue | SPEAKER MANAGER
02/01/2017 6:16am PST

Hi Seth,
This is a 2-day training course.

Picture of Seth Luersen
02/01/2017 6:14am PST

Is this a two day or one day course?

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
01/11/2017 1:17am 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 11:47am PST

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