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The Evolution of Data Science, Data Engineering, and AI

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Manage episode 206639107 series 1427720
Content provided by O'Reilly Radar. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by O'Reilly Radar 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 episode of the Data Show marks our 100th episode. This podcast stemmed out of video interviews conducted at O’Reilly’s 2014 Foo Camp. We had a collection of friends who were key members of the data science and big data communities on hand and we decided to record short conversations with them. We originally conceived of using those initial conversations to be the basis of a regular series of video interviews. The logistics of studio interviews proved too complicated, but those Foo Camp conversations got us thinking about starting a podcast, and the Data Show was born. To mark this milestone, my colleague Paco Nathan, co-chair of Jupytercon, turned the tables on me and asked me questions about previous Data Show episodes. In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. I’m proud of how this show has reached so many people across the world, and I’m looking forward to sharing more conversations in the future.
  continue reading

443 episodes

Artwork
iconShare
 
Manage episode 206639107 series 1427720
Content provided by O'Reilly Radar. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by O'Reilly Radar 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 episode of the Data Show marks our 100th episode. This podcast stemmed out of video interviews conducted at O’Reilly’s 2014 Foo Camp. We had a collection of friends who were key members of the data science and big data communities on hand and we decided to record short conversations with them. We originally conceived of using those initial conversations to be the basis of a regular series of video interviews. The logistics of studio interviews proved too complicated, but those Foo Camp conversations got us thinking about starting a podcast, and the Data Show was born. To mark this milestone, my colleague Paco Nathan, co-chair of Jupytercon, turned the tables on me and asked me questions about previous Data Show episodes. In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. I’m proud of how this show has reached so many people across the world, and I’m looking forward to sharing more conversations in the future.
  continue reading

443 episodes

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