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Stephanie Glen
  • Female
  • Jacksonville, FL
  • United States
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Profile Information

Short Bio:
Stephanie Glen is Editorial director at DataScienceCentral.com. She is a mathematician and statistician. After working for several years teaching mathematics and statistics at the university level, she created and developed the website StatisticsHowTo.com.
Company:
Andale Publishing, LLC
Job Title:
CEO
Seniority:
Executive
Job Function:
Other
Industry:
Mathematics Education
Interests:
Contributing

Stephanie Glen's Blog

AI: The Next Great Art Forger

Posted on May 9, 2021 at 2:30pm 0 Comments

  • AI develops new “art” using image analysis.
  • GANs do not create, they repaint.
  • The result is a pastiche, a poor copy of the real thing.

 

AI art is created with algorithms that enable AI to learn a specific aesthetic by analyzing thousands of images; The algorithm then…

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The Opioid Epidemic and Ethical Data Warehousing

Posted on April 30, 2021 at 8:14am 0 Comments

 

  • Data science and ML is being used to tackle the ongoing opioid epidemic.
  • Medical databases are rich with information but lack informed consent.
  • Problems of heterogeneous data and ethical concerns pose significant challenges,
  • Social media mining is emerging as a tool, but has its ethical problems as…
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Why you should put Fixed Point Strategies in Your Toolbox

Posted on April 25, 2021 at 6:00am 0 Comments

  • Fixed point strategies can approximate infinite depth.
  • The methods are easy to…
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Unusual Applications of Data Science

Posted on April 18, 2021 at 1:00pm 0 Comments

  • A round up of unusual applications of data science from recent academic journals,
  • Four examples far outside the usual realm of finance, professional services, and IT.
  • Applications range from tracking surgical tools to assessing suicide risk.

Tens of thousands data science research articles are published each year in…

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At 3:52am on December 11, 2019, Jason Posavad said…

Your article is so relevant Stephanie, as I am 48 and contemplating an online masters in Data Science.  My answer has been to do as much as I can through MOOCs, self-driven projects, and other less-expensive learning.  If it gets to the point that I have done all of that and proven to myself that I can do Data Science, and that I need a degree to get land a job, I will then do it.   Reality is you do need to be more careful and more risk-averse as you age, as the time to recover from mistakes is just not there anymore.  

 
 
 

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