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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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Just Fetch the Data and then... // David Bayliss // Coffee Sessions #110

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Manage episode 335807889 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 #110 with David Bayliss, Chief Data Scientist of LexisNexis Risk Solutions, Just Fetch the Data and then... co-hosted by Vishnu Rachakonda.
// Abstract
Composing data to extract features can be a significant problem. Key factors are the data size, compliance restrictions, and real-time data. Ethics (and law) can drive extremely complex audit requirements. In the cloud, you can do anything - at a price.
// Bio
One of the creators of the world's first big data platform (HPCC); David has been tackling big data problems for two decades. A mathematician, compiler writer, and data sponge with more than five dozen patents spanning platforms linking, and search.
Most inventors think outside the box; David can't even remember where the box is. He leads the team that creates their core Data Science methods used by hundreds of data scientists.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs

MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Interesting insight in this post. Would be cool to learn from David about his view on things
https://www.google.com/url?q=https://www.linkedin.com/posts/david-bayliss-426556a_datascience-platform-portability-activity-6913448643303759872-2dqq?utm_source%3Dlinkedin_share%26utm_medium%3Dmember_desktop_web&sa=D&source=calendar&ust=1649078059106132&usg=AOvVaw26wAevExeEfW_AdZSA8UhF
--------------- ✌️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 Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/
Connect with David on LinkedIn: https://www.linkedin.com/in/david-bayliss-426556a/
Timestamps:
[00:00] Introduction to David Bayliss
[01:03] Takeaways
[04:56] LexisNexis and David's role
[07:15] Evolution of LexisNexis in 20 years with so many use cases
[08:51] Role of David in structuring data for working with data change
[14:32] Data management and data access
[17:45] Unique challenges of scale, use case, and diversity at LexisNexis
[24:47] Tardis Iron Box
[30:05] Iron Box translation
[32:56] JVM for data science
[34:24] Iron Box meaning
[36:52] Metadata with PII
[39:08] Detrimental privacy / Hairy Kneecap Theory
[40:57] Speeding things up and Anonymized linking
[46:47] What kept David working at LexisNexis?
[50:30] Wrap up

  continue reading

329 bölüm

Artwork
iconPaylaş
 
Manage episode 335807889 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 #110 with David Bayliss, Chief Data Scientist of LexisNexis Risk Solutions, Just Fetch the Data and then... co-hosted by Vishnu Rachakonda.
// Abstract
Composing data to extract features can be a significant problem. Key factors are the data size, compliance restrictions, and real-time data. Ethics (and law) can drive extremely complex audit requirements. In the cloud, you can do anything - at a price.
// Bio
One of the creators of the world's first big data platform (HPCC); David has been tackling big data problems for two decades. A mathematician, compiler writer, and data sponge with more than five dozen patents spanning platforms linking, and search.
Most inventors think outside the box; David can't even remember where the box is. He leads the team that creates their core Data Science methods used by hundreds of data scientists.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs

MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Interesting insight in this post. Would be cool to learn from David about his view on things
https://www.google.com/url?q=https://www.linkedin.com/posts/david-bayliss-426556a_datascience-platform-portability-activity-6913448643303759872-2dqq?utm_source%3Dlinkedin_share%26utm_medium%3Dmember_desktop_web&sa=D&source=calendar&ust=1649078059106132&usg=AOvVaw26wAevExeEfW_AdZSA8UhF
--------------- ✌️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 Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/
Connect with David on LinkedIn: https://www.linkedin.com/in/david-bayliss-426556a/
Timestamps:
[00:00] Introduction to David Bayliss
[01:03] Takeaways
[04:56] LexisNexis and David's role
[07:15] Evolution of LexisNexis in 20 years with so many use cases
[08:51] Role of David in structuring data for working with data change
[14:32] Data management and data access
[17:45] Unique challenges of scale, use case, and diversity at LexisNexis
[24:47] Tardis Iron Box
[30:05] Iron Box translation
[32:56] JVM for data science
[34:24] Iron Box meaning
[36:52] Metadata with PII
[39:08] Detrimental privacy / Hairy Kneecap Theory
[40:57] Speeding things up and Anonymized linking
[46:47] What kept David working at LexisNexis?
[50:30] Wrap up

  continue reading

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