Nike Tech Talks
December 
14
 at 
4:30pm
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My education was focused on the earth sciences (geophysics, carbonate geology) and computer science (data analytics); and previous work experience was geared toward data science and plug-in development for the energy industry. Technical skills: Python (10 years) and R (4 years), with 2 years' experience building data science products using Hadoop and its associated dongles (especially Spark). When I'm not sitting in front of glowing rectangular screens at work, I absolutely adore hiking / kayaking / mountain-biking around Texas' glorious Green Belt; resuscitating Apples; and (poorly!) attempting to play bass guitar. Personal passions are sustainable energy and climate change research; STEM education reform; and empowering local governments via data science https://twitter.com/DynamicWebPaige

My education was focused on the earth sciences (geophysics, carbonate geology) and computer science (data analytics); and previous work experience was geared toward data science and plug-in development for the energy industry. Technical skills: Python (10 years) and R (4 years), with 2 years' experience building data science products using Hadoop and its associated dongles (especially Spark). When I'm not sitting in front of glowing rectangular screens at work, I absolutely adore hiking / kayaking / mountain-biking around Texas' glorious Green Belt; resuscitating Apples; and (poorly!) attempting to play bass guitar. Personal passions are sustainable energy and climate change research; STEM education reform; and empowering local governments via data science https://twitter.com/DynamicWebPaige

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Dec 
14
 at 
4:30PM

Nike Tech Talks

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Join Microsoft senior cloud developer advocate Paige Bailey at the next Nike Tech Talks on March 22! Paige will give a talk titled, Predicting Clothing Styles with Deep Transfer Learning.


Food and beverages will be served and there will be time to network before and after the talk.

Featured Speaker

PAIGE BAILEY

My education was focused on the earth sciences (geophysics, carbonate geology) and computer science (data analytics); and previous work experience was geared toward data science and plug-in development for the energy industry. Technical skills: Python (10 years) and R (4 years), with 2 years' experience building data science products using Hadoop and its associated dongles (especially Spark). When I'm not sitting in front of glowing rectangular screens at work, I absolutely adore hiking / kayaking / mountain-biking around Texas' glorious Green Belt; resuscitating Apples; and (poorly!) attempting to play bass guitar. Personal passions are sustainable energy and climate change research; STEM education reform; and empowering local governments via data science.

Event schedule

4:30PM

Check-In, Networking, Food & Drinks

5:00PM

Talk: Predicting Clothing Styles with Deep Transfer Learning

6:00PM

Networking, Food & Drinks

ABSTRACT

In this talk, we'll use image recognition to take an existing deep learning model and adapt it to a specialized domain (namely: guessing whether articles of clothing are preppy, sporty, punk, etc.). Instead of using a more intensive data classifier, like a Residual Network, we'll use deep transfer learning to overcome a data scarcity problem and build on top of an existing model.


Once the transfer learning model has been trained, we'll pack it up into a dockerized container (specifying inputs and outputs, as well as a score.py file), and then call it as a web service. We will also discuss a #DataOps process for refreshing the model as trends change over time. 

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