Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY

In-Person Training
Deep learning with TensorFlow

Dana Mastropole (The Data Incubator)
Monday, June 26 & Tuesday, June 27, 9:00am - 5:00pm
Location: Madison
Secondary topics:  Deep Learning
Average rating: ***..
(3.50, 2 ratings)

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

Dana Mastropole demonstrates TensorFlow's deep learning capabilities through its Python interface as she 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.

Dana Mastropoles demonstrate TensorFlow’s deep learning capabilities through its Python interface as she 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 Dana Mastropole

Dana Mastropole is a data scientist in residence at the Data Incubator and contributes to curriculum development and instruction. Previously, Dana taught elementary school science after completing MIT’s Kaufman teaching certificate program. She studied physics as an undergraduate student at Georgetown University and holds a master’s in physical oceanography from MIT.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.

Leave a Comment or Question

Help us make this conference the best it can be for you. Have questions you'd like this speaker to address? Suggestions for issues that deserve extra attention? Feedback that you'd like to share with the speaker and other attendees?

Join the conversation here (requires login)

Comments

Marcin Dziduch | DATA SCIENTIST
08/16/2017 11:42pm EDT

Hey Dana,

Thanks for great tutorial.
Could you please forward to me certificate of completion of TF course?

Thanks,

Marcin

Picture of Dana Mastropole
Dana Mastropole | DATA SCIENTIST IN RESIDENCE
06/25/2017 12:23pm EDT

Hi, sorry for the confusion. We will be doing things a little differently than stated in the email. When you arrive at the training, we will give you the IP address and password to a DigitalOcean box. Your box will contain all of the course material and have all of the necessary software already installed. It is okay to use a windows laptop.

Bharath Kumar | BIGDATA LEAD
06/23/2017 3:54pm EDT

A couple of questions/clarifications:
Will a Windows Laptop work?
What version of Python and Tensor flow need to installed? The email states that a docker will be provided – will this docker contain Python and TensorFlow?

Picture of Dana Mastropole
Dana Mastropole | DATA SCIENTIST IN RESIDENCE
06/19/2017 6:44am EDT

We will pass out the necessary login information at the conference.

Picture of Robert Roush
Robert Roush | MFG SYSTEMS MANAGER
06/13/2017 12:26pm EDT

Will curriculum material and docker container still be provided prior to the conference? If so, any idea when?
Thanks.

Jorge Luna | GRADUATE STUDENT
06/08/2017 9:33am EDT

Please expand the seats available?

Steven Rutherford |
05/24/2017 11:08am EDT

Are there still seats open for this training? Would like to know before purchasing a package.

Picture of Dana Mastropole
Dana Mastropole | DATA SCIENTIST IN RESIDENCE
05/24/2017 5:34am EDT

Correction – Having Chrome or Firefox installed.

Picture of Dana Mastropole
Dana Mastropole | DATA SCIENTIST IN RESIDENCE
05/24/2017 5:32am EDT
  • We will use TensorFlow version 1.1.0.
  • We will mostly be working with the MNIST dataset, but there is no need to download it in advance.
  • The only technical requirement is having Safari or Chrome installed on your machine.
Marcin Dziduch | DATA SCIENTIST
05/24/2017 12:24am EDT

Hey speakers,

Few technical questions:

Which version of TF we will use?
Which dataset we will be training on? Possibly to download prior to the tutorial.
Other technical details if any, i.e.: other python packages etc.

Thanks in advance

Ajibola Obayemi | DATA AND KNOWLEDGE SYSTEMS DEVELOPER
05/18/2017 11:51am EDT

Hi Patrick Dirden,

Can I get enrolled as well? I really want to attend this training and it is the basis for registering in the first place. I have completed my registration and it says the Deep Learning with TensorFlow class was filled. Kindly let me know. Thanks

Picture of Patrick Dirden
Patrick Dirden | REGISTRATION MANAGER
05/15/2017 10:04am EDT

Bernard, we secured an additional seat, and you are now enrolled in Deep learning with TensorFlow!

Bernard Ong | DATA SCIENTIST
05/11/2017 7:22pm EDT

I really wanted to attend this, but it’s says it’s already all booked. Any chance to still get one in?

Salil Jain | SENIOR SECURITY ADVISOR
04/20/2017 10:14am EDT

I have prelim working understanding of TensorFlow. Will this training cover advanced topics to be worthwhile?

Picture of Robert Schroll
Robert Schroll | DATA SCIENTIST IN RESIDENCE
03/29/2017 9:50am EDT

We’ll discuss RNNs in general, and we’ll go through a particular example using an LSTM network.

Jonathan Corey | ANALYTICS MODELER
03/29/2017 8:32am EDT

Will this training include the use of RNNs on time series data or is it mentioned just as a possible application?