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How to Test ML Code - ML 091

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Manage episode 344810618 series 2977446
Content provided by Charles M Wood. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Charles M Wood 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.
In this show, we cover some practical tips for writing reliable ML code. Here are some of the questions we look to answer...
  1. What are tests and why should you use them?
  2. What's the difference between unit tests and integration tests?
  3. What should you test?
  4. How should you write tests in python? (the answer is to use pytest)

Sponsors
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
  continue reading

168 episodes

Artwork
iconShare
 
Manage episode 344810618 series 2977446
Content provided by Charles M Wood. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Charles M Wood 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.
In this show, we cover some practical tips for writing reliable ML code. Here are some of the questions we look to answer...
  1. What are tests and why should you use them?
  2. What's the difference between unit tests and integration tests?
  3. What should you test?
  4. How should you write tests in python? (the answer is to use pytest)

Sponsors
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
  continue reading

168 episodes

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