Machine learning at small organizations
Podcast |
Practical AI: Machine Learning, Data Science
Publisher |
Changelog Media
Media Type |
audio
Podknife tags |
Artificial Intelligence, 
Business, 
Data Science, 
Interview, 
Machine Learning, 
Tech News, 
Technology
Categories Via RSS |
Software How-To, 
Tech News, 
Technology
Publication Date |
Jan 17, 2023
Episode Duration |
00:49:51
Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.
Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.

Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.

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Featuring:

Show Notes:

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Timestamps:

(00:00) - Opener(00:37) - Welcome to Practical AI(01:12) - Kirsten Lum(05:44) - Selling short in data science(08:02) - FUD from a management POV(13:44) - Data science is like cooking(17:32) - Sponsor: The Changelog(19:16) - What to focus on when you're new(22:33) - Managing flexibility in a small company(26:26) - Navigating people in a small business(29:17) - Putting the practical in PracticalAI(35:54) - How to approach non data-centric people(39:26) - Advantages of small ML orgs over big orgs(42:37) - Mentoring people the right way(46:00) - Looking into the future(49:04) - Outro

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