Becoming a machine learning practitioner

The O’Reilly Data Show Podcast: Kesha Williams on how she added machine learning to her software developer toolkit.

By Ben Lorica
August 29, 2019
Binary Binary (source: Martin Vorel on LibreShot)

Becoming a machine learning practitioner
Data Show Podcast

00:00 / 00:33:22

In this episode of the Data Show, I speak with Kesha Williams, technical instructor at A Cloud Guru, a training company focused on cloud computing. As a full stack web developer, Williams became intrigued by machine learning and started teaching herself the ML tools on Amazon Web Services. Fast forward to today, Williams has built some well-regarded Alexa skills, mastered ML services on AWS, and has now firmly added machine learning to her developer toolkit.

Anatomy of an Alexa Skill
Anatomy of an Alexa skill. Image by Kesha Williams, used with permission.

We had a great conversation spanning many topics, including:

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  • How she got started and made the transition into a full-fledged machine learning practitioner.
  • We discussed the evolution of ML tools and learning resources, and how accessible they’ve become for developers.
  • How to build and monetize Alexa skills. Along the way, we took a deep dive and discussed some of the more interesting Alexa skills she has built, as well as one that she really admires.

Related resources:

Post topics: AI & ML, Data, O'Reilly Data Show Podcast
Post tags: Podcast

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