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İçerik Demetrios Brinkmann tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Demetrios Brinkmann veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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Scaling Machine Learning with Data Mesh // Shawn Kyzer // Coffee Sessions #116

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Manage episode 338103156 series 3241972
İçerik Demetrios Brinkmann tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Demetrios Brinkmann veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

MLOps Coffee Sessions #116 with Shawn Kyzer, Principal Data Engineer at Thoughtworks (Spain), Scaling Machine Learning with Data Mesh co-hosted by Adam Sroka.
// Abstract
You can't just get something done by using tools. You need to go much deeper than that and it is very clear that Data Mesh is the same thing. You have to educate the organization about the movement.
In this session, Shawn broke down the cultural piece of data mesh and how many parallels there are with the MLOps Movement when it comes to the cultural side of MLOps.
// Bio
Shawn is passionate about harnessing the power of data strategy, engineering, and analytics in order to help businesses uncover new opportunities. As an innovative technologist with over 13 years of experience, Shawn removes technology as a barrier and broadens the art of the possible for business and product leaders. His holistic view of technology and emphasis on developing and motivating strong engineering talent, with a focus on delivering outcomes whilst minimising outputs, is one of the characteristics which sets him apart from the crowd.
Shawn’s deep technical knowledge includes distributed computing, cloud architecture, data science, machine learning, and engineering analytics platforms. He has years of experience working as a consultant practitioner for a variety of prestigious clients ranging from secret clearance level government organizations to Fortune 500 companies.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
https://odsc.com/speakers/scaling-machine-learning-with-data-mesh/ https://docs.google.com/presentation/d/1rVtltHkRkP_JaGZdkAS3U_SXfr5Gg-RP980FKXh0YNU/edit?usp=sharing
--------------- ✌️Connect With Us ✌️ -------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Catch all episodes, blogs, newsletters, and more: https://mlops.community/
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Adam on LinkedIn: https://www.linkedin.com/in/aesroka/
Connect with Shawn on LinkedIn: https://www.linkedin.com/in/shawn-kyzer-msit-mba-b5b8a4b/
Timestamps:
[00:00] Introduction to Shawn Kyzer
[00:43] Takeaways
[04:00] Data Mesh for ML projects
[11:22] The signal for the exploratory part of a new modeling project
[14:13] Ownership and centralization
[16:20] Lack of technology and some implementations literature
[17:10] Python stronghold from Microsoft blogs
[23:09] Integration with self-serve data platform
[25:31] Starting a platform team
[30:04] Quick wins
[32:09] Metrics monitoring
[34:18] Metrics break up
[38:32] Limit to capabilities and not worth doing
[41:39] Culture and technology holds
[44:03] Setting the foundation
[46:53] Unforeseen benefits
[52:19] Lightning question

  continue reading

326 bölüm

Artwork
iconPaylaş
 
Manage episode 338103156 series 3241972
İçerik Demetrios Brinkmann tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Demetrios Brinkmann veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

MLOps Coffee Sessions #116 with Shawn Kyzer, Principal Data Engineer at Thoughtworks (Spain), Scaling Machine Learning with Data Mesh co-hosted by Adam Sroka.
// Abstract
You can't just get something done by using tools. You need to go much deeper than that and it is very clear that Data Mesh is the same thing. You have to educate the organization about the movement.
In this session, Shawn broke down the cultural piece of data mesh and how many parallels there are with the MLOps Movement when it comes to the cultural side of MLOps.
// Bio
Shawn is passionate about harnessing the power of data strategy, engineering, and analytics in order to help businesses uncover new opportunities. As an innovative technologist with over 13 years of experience, Shawn removes technology as a barrier and broadens the art of the possible for business and product leaders. His holistic view of technology and emphasis on developing and motivating strong engineering talent, with a focus on delivering outcomes whilst minimising outputs, is one of the characteristics which sets him apart from the crowd.
Shawn’s deep technical knowledge includes distributed computing, cloud architecture, data science, machine learning, and engineering analytics platforms. He has years of experience working as a consultant practitioner for a variety of prestigious clients ranging from secret clearance level government organizations to Fortune 500 companies.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
https://odsc.com/speakers/scaling-machine-learning-with-data-mesh/ https://docs.google.com/presentation/d/1rVtltHkRkP_JaGZdkAS3U_SXfr5Gg-RP980FKXh0YNU/edit?usp=sharing
--------------- ✌️Connect With Us ✌️ -------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Catch all episodes, blogs, newsletters, and more: https://mlops.community/
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Adam on LinkedIn: https://www.linkedin.com/in/aesroka/
Connect with Shawn on LinkedIn: https://www.linkedin.com/in/shawn-kyzer-msit-mba-b5b8a4b/
Timestamps:
[00:00] Introduction to Shawn Kyzer
[00:43] Takeaways
[04:00] Data Mesh for ML projects
[11:22] The signal for the exploratory part of a new modeling project
[14:13] Ownership and centralization
[16:20] Lack of technology and some implementations literature
[17:10] Python stronghold from Microsoft blogs
[23:09] Integration with self-serve data platform
[25:31] Starting a platform team
[30:04] Quick wins
[32:09] Metrics monitoring
[34:18] Metrics break up
[38:32] Limit to capabilities and not worth doing
[41:39] Culture and technology holds
[44:03] Setting the foundation
[46:53] Unforeseen benefits
[52:19] Lightning question

  continue reading

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