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Building the world's most popular data science platform (Practical AI #101)

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Content provided by Changelog Media. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Changelog Media 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.

Everyone working in data science and AI knows about Anaconda and has probably “conda” installed something. But how did Anaconda get started and what are they working on now? Peter Wang, CEO of Anaconda and creator of PyData and popular packages like Bokeh and DataShader, joins us to discuss that and much more. Peter gives some great insights on the Python AI ecosystem and very practical advice for scaling up your data science operation.

Join the discussion

Changelog++ members get a bonus 2 minutes at the end of this episode and zero ads. Join today!

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  • DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
  • Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Let’s do this!
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Featuring:

Show Notes:

Something missing or broken? PRs welcome!

  continue reading

2359 episodes

Artwork
iconShare
 

Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on December 15, 2025 20:12 (24h ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 269804246 series 1280399
Content provided by Changelog Media. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Changelog Media 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.

Everyone working in data science and AI knows about Anaconda and has probably “conda” installed something. But how did Anaconda get started and what are they working on now? Peter Wang, CEO of Anaconda and creator of PyData and popular packages like Bokeh and DataShader, joins us to discuss that and much more. Peter gives some great insights on the Python AI ecosystem and very practical advice for scaling up your data science operation.

Join the discussion

Changelog++ members get a bonus 2 minutes at the end of this episode and zero ads. Join today!

Sponsors:

  • DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
  • Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Let’s do this!
  • FastlyOur bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
  • RollbarWe move fast and fix things because of Rollbar. Resolve errors in minutes. Deploy with confidence. Learn more at rollbar.com/changelog.

Featuring:

Show Notes:

Something missing or broken? PRs welcome!

  continue reading

2359 episodes

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