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#142 From PhD drop-out to Google Data Scientist with Megan Risdal

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Manage episode 440901318 series 3513743
Contenu fourni par Quincy Larson. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Quincy Larson ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

On this week's episode of the podcast, freeCodeCamp founder Quincy Larson interviews Meg Risdal. She's a data scientist and Product Manager at Kaggle, Google's Data Science competition platform.

Megan works closely with the global data science community, and on Google's Gemma open models project.

We talk about:

- Google's Kaggle, which hosts 300k open data sets and runs data science competitions each week that anyone can participate in.

- How people talk in academia VS how people talk in tech

- Stack Overflow VS Kaggle – how Megan contrasts what it was like to work on these two "communities of practice"

- Linguistics and its importance in LLMs and AI research

Can you recognize the song I'm playing during the intro? It's a punk song from 1994.

Be sure to follow The freeCodeCamp podcast in your favorite podcast app. And share this podcast with a friend. Let's inspire more folks to learn to code and build careers for themselves in tech.

Also, I want to thank the 10,779 kind people who support our charity each month, and who make this podcast possible. You can join them and support our mission at: https://www.freecodecamp.org/donate

Links we talk about during our conversation:

Meg's blog: https://www.meg.dev/

The Sliced Data Science Gameshow that Meg co-hosted with Nick Wan: https://www.youtube.com/playlist?list=PL6PX3YIZuHhyQmXKnyZmVDzdgAYbzwgDw

Meg on Twitter: https://twitter.com/MeganRisdal

Kaggle's open learning resources: https://www.kaggle.com/learn

The Gemma team at Google that Meg also works on: https://ai.google.dev/gemma

  continue reading

120 episodes

Artwork
iconPartager
 
Manage episode 440901318 series 3513743
Contenu fourni par Quincy Larson. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Quincy Larson ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

On this week's episode of the podcast, freeCodeCamp founder Quincy Larson interviews Meg Risdal. She's a data scientist and Product Manager at Kaggle, Google's Data Science competition platform.

Megan works closely with the global data science community, and on Google's Gemma open models project.

We talk about:

- Google's Kaggle, which hosts 300k open data sets and runs data science competitions each week that anyone can participate in.

- How people talk in academia VS how people talk in tech

- Stack Overflow VS Kaggle – how Megan contrasts what it was like to work on these two "communities of practice"

- Linguistics and its importance in LLMs and AI research

Can you recognize the song I'm playing during the intro? It's a punk song from 1994.

Be sure to follow The freeCodeCamp podcast in your favorite podcast app. And share this podcast with a friend. Let's inspire more folks to learn to code and build careers for themselves in tech.

Also, I want to thank the 10,779 kind people who support our charity each month, and who make this podcast possible. You can join them and support our mission at: https://www.freecodecamp.org/donate

Links we talk about during our conversation:

Meg's blog: https://www.meg.dev/

The Sliced Data Science Gameshow that Meg co-hosted with Nick Wan: https://www.youtube.com/playlist?list=PL6PX3YIZuHhyQmXKnyZmVDzdgAYbzwgDw

Meg on Twitter: https://twitter.com/MeganRisdal

Kaggle's open learning resources: https://www.kaggle.com/learn

The Gemma team at Google that Meg also works on: https://ai.google.dev/gemma

  continue reading

120 episodes

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