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Catherine Nelson & Hannes Hapke: Building ML Pipelines #114

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Manage episode 276069909 series 2526207
Content provided by Sanyam Bhutani. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sanyam Bhutani 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://staging.podcastplayer.com/legal.

Video Version: https://youtu.be/wxVGu8vKvG8

Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani

In this episode, Sanyam Bhutani interviews the authors of the book "Building ML Pipelines": Catherine Nelson and Hannes Hapke

Catherine is a data scientist at SAP concur labs. And Hannes is an ML Engineer in the same company.

They talk about the journey into machine learning and the journey into this world of building machine learning pipelines, they dive into depth about the book, covering:

- Who's the book really for?

- What does it cover?

- What can you expect out of it?

Links:

https://www.buildingmlpipelines.com

Follow:

Catherine Nelson:

https://twitter.com/drcatnelson

Hannes Hapke:

https://twitter.com/hanneshapke

hanneshapke.github.io

Sanyam Bhutani:

https://twitter.com/bhutanisanyam1

Blog: sanyambhutani.com

About:

https://sanyambhutani.com/tag/chaitimedatascience/

A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

You can expect weekly episodes every available as Video, Podcast, and blogposts.

Intro track:

Flow by LiQWYD https://soundcloud.com/liqwyd

  continue reading

149 episodes

Artwork
iconShare
 
Manage episode 276069909 series 2526207
Content provided by Sanyam Bhutani. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sanyam Bhutani 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://staging.podcastplayer.com/legal.

Video Version: https://youtu.be/wxVGu8vKvG8

Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani

In this episode, Sanyam Bhutani interviews the authors of the book "Building ML Pipelines": Catherine Nelson and Hannes Hapke

Catherine is a data scientist at SAP concur labs. And Hannes is an ML Engineer in the same company.

They talk about the journey into machine learning and the journey into this world of building machine learning pipelines, they dive into depth about the book, covering:

- Who's the book really for?

- What does it cover?

- What can you expect out of it?

Links:

https://www.buildingmlpipelines.com

Follow:

Catherine Nelson:

https://twitter.com/drcatnelson

Hannes Hapke:

https://twitter.com/hanneshapke

hanneshapke.github.io

Sanyam Bhutani:

https://twitter.com/bhutanisanyam1

Blog: sanyambhutani.com

About:

https://sanyambhutani.com/tag/chaitimedatascience/

A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

You can expect weekly episodes every available as Video, Podcast, and blogposts.

Intro track:

Flow by LiQWYD https://soundcloud.com/liqwyd

  continue reading

149 episodes

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YT Channel: https://www.youtube.com/@ChaiTimeDataScience Learn more about H2O's Hydrogen Torch app here: https://h2o.ai/platform/ai-cloud/make/hydrogen-torch/ In this "episode", Sanyam Bhutani will host the the world's top kagglers and best data scientists to learn and debate the best practises for training ml models. We will learn from their experience of having won multiple competitions and built many incredible products at H2O: what are the best practises for taming your ml model Panelists: Dmitry Gordeev: https://www.kaggle.com/dott1718 https://twitter.com/dott1718 https://www.linkedin.com/in/dmitry-gordeev-50116023/?originalSubdomain=at Gabor Fodor: https://www.kaggle.com/gaborfodor https://www.linkedin.com/in/gábor-fodor-6a081548/?originalSubdomain=hu Pascal Pfeiffer: https://www.kaggle.com/ilu000 https://www.linkedin.com/in/pascal-pfeiffer/ Philipp Singer: https://www.kaggle.com/philippsinger https://twitter.com/ph_singer https://www.linkedin.com/in/philippsinger/ Yauhen Babakhin: https://www.kaggle.com/ybabakhin https://www.linkedin.com/in/yauhenbabakhin/ Sanyam Bhutani: https://www.kaggle.com/init27 https://twitter.com/bhutanisanyam1 https://www.linkedin.com/in/sanyambhutani/ A show for interviews with Practitioners, Kagglers & Researchers hosted by Sanyam.…
 
Channel: http://youtube.com/c/ChaiTimeDataScience/ Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this Episode, Sanyam Bhutani interviews Amed Coulibaly about his journey and reflection on reaching Kaggle Competitions Grandmaster. They also understand his team's 3rd place solution to recently ended Feedback competition Links: Solution: https://www.kaggle.com/competitions/feedback-prize-english-language-learning/discussion/369609 Follow: Amed Coulibaly: Twitter: https://twitter.com/Amedprof Linkedin: https://www.linkedin.com/in/amed-coulibaly-94150610a/ Kaggle: https://www.kaggle.com/amedprof Sanyam Bhutani: Twitter: https://twitter.com/bhutanisanyam1 LinkedIn: https://www.linkedin.com/in/sanyambhutani/ Kaggle: https://www.kaggle.com/init27 Blog: sanyambhutani.com A show for Interviews with Practitioners, Kagglers & Researchers, and all things Data Science hosted by Sanyam Bhutani.…
 
The show becomes "Coffee Time Data Science" for a one-time special episode! The genesis for this interview was this twitter thread: https://twitter.com/jeremyphoward/status/1503920390447730690 Video version: https://www.youtube.com/watch?v=g_6nQBsE4pU Links from the show: fastai Course: https://course.fast.ai How not to do fastai: https://medium.com/@init_27/how-not-to-do-fast-ai-or-any-ml-mooc-3d34a7e0ab8c Meta Learning Book: https://radekosmulski.gumroad.com/l/learn_deep_learning Rachel’s advice on Blogging: https://medium.com/@racheltho/why-you-yes-you-should-blog-7d2544ac1045 In the frame: Jeremy Howard: https://twitter.com/jeremyphoward Sanyam Bhutani: https://twitter.com/bhutanisanyam1 OUTLINE: 0:00 - Intro 2:40 - Reaching Kaggle Grandmaster Tier 4:46 - Current Work 6:30 - University Education 12:00 - Signing up for fastai 15:49 - Failures with fastai 18:29 - Tenacity 23:40 - Content Creation 33:10 - Sharing your work 36:09 - Educational Content 41:49 - Failing Google AI Residency 46:34 - Starting the podcast 48:19 - Question to Jeremy 52:40 - Thank you…
 
Video Version: https://youtu.be/qObfeWYbrPM In this episode, Sanyam Bhutani interviews the hosts from AI Today Podcast: Kathleen Walch, Ronald Schmelzer They talk about their journey into AI, creating AI Content, and the AI Today Podcast. Links: AI Today Podcast: https://www.cognilytica.com/aitoday/ Cognalytica: https://www.cognilytica.com Follow: Kathleen Walch: Twitter: https://twitter.com/kath0134 Linkedin: https://www.linkedin.com/in/kathleen-walch-50185112/ Ronald Schmelzer: Twitter: https://twitter.com/rschmelzer Linkedin: https://www.linkedin.com/in/rschmelzer/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.…
 
Video Version: https://youtu.be/W3aWEXqIkWk Blog Overview: http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this Episode, Sanyam Bhutani interviews a panel from the ACM RecSys Winning competition team at NVIDIA. They explain why are RecSys systems such a hard problem, how can GPUs accelerate these, how do we productize such solutions. The team also does a ground basic to a complete overview of their solution. They understand the team's approaches to the problem, how did they arrive at the solution, and the tricks that they discovered and very generously shared in this interview Links: Interview with Even Oldridge: https://youtu.be/-WzXIV8P_Jk Interview with Chris Deotte: https://youtu.be/QGCvycOXs2M Open Source Solution: https://github.com/NVIDIA-Merlin/competitions/tree/main/RecSys2021_Challenge Paper Link: https://github.com/NVIDIA-Merlin/competitions/blob/main/RecSys2021_Challenge/GPU-Accelerated-Boosted-Trees-and-Deep-Neural-Networks-for-Better-Recommender-Systems.pdf Follow: Benedikt Schifferer: Linkedin: https://www.linkedin.com/in/benedikt-schifferer/ Bo Liu: Twitter: https://twitter.com/boliu0 Kaggle: https://www.kaggle.com/boliu0 Chris Deotte: Twitter: https://twitter.com/ChrisDeotte Kaggle: https://www.kaggle.com/cdeotte Even Oldridge Twitter: https://twitter.com/even_oldridge Linkedin: https://www.linkedin.com/in/even-oldridge/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers, and all things Data Science hosted by Sanyam Bhutani.…
 
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