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Put AI to work
September 17-18, 2017: Training
September 18-20, 2017: Tutorials & Conference
San Francisco, CA

In-Person Training
Deep learning with TensorFlow

Robert Schroll (The Data Incubator)
Sunday, September 17 & Monday, September 18, 9:00am - 5:00pm
Location: Franciscan A
Average rating: ***..
(3.67, 3 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 Monday.

Robert Schroll demonstrates TensorFlow's deep learning capabilities through its Python interface as he walks you through building machine learning algorithms piece by piece and implementing neural networks using TFLearn. Along the way, you'll explore several real-world deep learning applications, including machine vision, text processing, and generative networks.

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

  • Understand TensorFlow’s strengths for machine learning
  • Learn how to build a basic computation within TensorFlow using Python and how to use TFLearn’s machine learning algorithms
  • Discover how TensorFlow can help with AI problems like object recognition and text processing to chat apps

Prerequisites:

  • Basic knowledge of Python

Hardware and/or installation requirements:

  • A laptop with TensorFlow installed (A Docker container will be provided.)

Many of the deep learning algorithms used in AI applications are powered by large matrix operations. TensorFlow provides data flow graphs for such operations, allowing algorithms to be easily parallelized across multiple processors or machines. This makes TensorFlow an ideal environment for implementing neural networks and other deep learning algorithms: convolutional neural networks can be used to provide object recognition for machine vision; recurrent neural networks, including long short-term memory architectures, allow the comprehension of time series and language; and generative networks give AI applications the ability to create output. The TensorFlow library provides for 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.

Robert Schroll demonstrates TensorFlow’s deep learning capabilities through its Python interface as he walks you through building machine learning algorithms piece by piece and implementing neural networks using TFLearn. Along the way, you’ll explore several real-world deep learning applications, including machine vision, text processing, and generative networks.

About your instructor

Photo of Robert Schroll

Robert Schroll is a 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

Ahmad Ghannam | SW DEVELOPER / ASSOCIATE ENGINEER
10/03/2017 2:57pm PDT

Hello !
When can we receive the videos for this course ?

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
09/14/2017 6:59am PDT

Safari Online has a lot of good Python resources; I’ve also found this site to be a good resource: http://www.siafoo.net/article/52

It’s a bit dated by now, but I learned much of Python knowledge from http://www.diveintopython.net/

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
09/14/2017 6:50am PDT

Hi all,

We will provide each of you with a fully-provisioned cloud computer, so you don’t need to worry about installing the correct version locally. All you’ll need is a laptop with a reasonably recent version of Chrome or Firefox.

At the end of the course, we’ll help you get all of the material download and give you some tips on setting up your own Python environment.

Madhavan "Madhu" Varadarajan | PRINCIPAL ARCHITECT
09/12/2017 2:44pm PDT

Jason, can you respond to my q?tx

Picture of Jason Perdue
Jason Perdue | SPEAKER MANAGER
09/12/2017 9:26am PDT
Samuel Yang |
09/12/2017 8:58am PDT

Any recommendations for a site that will provide the requisite “basic knowledge of Python”?

Madhavan "Madhu" Varadarajan | PRINCIPAL ARCHITECT
09/12/2017 7:40am PDT

Hello,

For tensor flow install, should I follow a specific mode i.e. “native” pip or Anaconda?

Picture of Jason Perdue
Jason Perdue | SPEAKER MANAGER
09/11/2017 7:20am PDT

The hardware requirements have been updated. There is no curriculum download necessary.

John Brahy | CTO
09/11/2017 5:02am PDT

Is there a link to the Curriculum material?

Jack Li | SOFTWARE ENGINEER
09/07/2017 12:24am PDT

I saw the class is already full, is there a plan to accommodate more spaces?

Neeraj J | DATA ENGINEER
09/01/2017 5:40am PDT

Is this class full ? Wondering if there is space for 1 more ? Please confirm.

Ahmad Ghannam | SW DEVELOPER / ASSOCIATE ENGINEER
08/22/2017 9:03pm PDT

Thanks !!

Picture of Jason Perdue
Jason Perdue | SPEAKER MANAGER
08/22/2017 2:50am PDT

We are adding a couple of seats right now.

Ahmad Ghannam | SW DEVELOPER / ASSOCIATE ENGINEER
08/21/2017 6:22pm PDT

It’s fully booked , is there any way to for registration ?

Picture of Jason Perdue
Jason Perdue | SPEAKER MANAGER
08/03/2017 1:40am PDT

Robert Schroll is scheduled to give this training.

Jasmi Patel | ANALYTICS DEVELOPER
08/02/2017 3:06pm PDT

Who is the instructor for this training ? Michael Li and Dana Mastropole OR Robert Schroll ?