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Re - Release: Machine Learning Technical Debt
Manage episode 233185745 series 74115
Content provided by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
This week, we've got a fun paper by our friends at Google about the hidden costs of maintaining machine learning workflows. If you've worked in software before, you're probably familiar with the idea of technical debt, which are inefficiencies that crop up in the code when you're trying to go fast. You take shortcuts, hard-code variable values, skimp on the documentation, and generally write not-that-great code in order to get something done quickly, and then end up paying for it later on. This is technical debt, and it's particularly easy to accrue with machine learning workflows. That's the premise of this episode's paper. https://ai.google/research/pubs/pub43146
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Manage episode 233185745 series 74115
Content provided by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
This week, we've got a fun paper by our friends at Google about the hidden costs of maintaining machine learning workflows. If you've worked in software before, you're probably familiar with the idea of technical debt, which are inefficiencies that crop up in the code when you're trying to go fast. You take shortcuts, hard-code variable values, skimp on the documentation, and generally write not-that-great code in order to get something done quickly, and then end up paying for it later on. This is technical debt, and it's particularly easy to accrue with machine learning workflows. That's the premise of this episode's paper. https://ai.google/research/pubs/pub43146
…
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Show notes are at https://stevelitchfield.com/sshow/chat.html
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continue reading
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…
continue reading
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
…
continue reading
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This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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continue reading
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