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Published 7 months, 1 week ago

Tech Amazon Published by J. Doe

A Q&A with Kesha Williams, AWS Machine Learning Hero

We recently sat down for a conversation with Kesha Williams to discuss her journey from "playing on the computer" to machine learning and recent events and activities she's supported—like Kesha leading a talk and a three-part "Machine learning (ML) for Social Good" training series with Women Who Code, that culminated in a hackathon which challenged participants to apply their ML skills to help address challenges caused by COVID-19.

When I was in the 11th grade, I went to a six-week summer science enrichment training program at a local college where I learned more about computers and chemistry.

Then three or four years ago I started dabbling with machine learning and found my second love. It's been a journey, just enjoying learning new things. What first got you interested in machine learning? What piqued your interest?When I first heard about machine learning, I found the technology to be exciting and scary at the same time. The way I'm wired, I love exploring and playing on the computer and learning new things. If it's something that I can grasp, I'll show you all of my lessons learned to jump start you to pick up where I left off and continue on.

What inspired you to lead this Machine Learning for Good hackathon with Women Who Code?I'm always challenging myself to learn new things and try new things. With machine learning, there are so many different learning algorithms and so many different machine learning techniques. So over the summer, I set a personal challenge for myself, and that was to use machine learning to battle COVID-19.

Original article

Sep 11, 2020 at 05:44


Video provided by Amazon.


Meet Kesha Williams - an A Cloud Guru Women Who Code Scholarship Winner


Mar 17, 2018 by A Cloud Guru


A Cloud Guru was proud to speak with Kesha Williams, a #WomenWhoCode scholarship winner and part of Amazon’s “Alexa Women of Voice”! Watch the video and read more about ACG’s We Power Tech at

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