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MLOps Coffee Sessions #146 with Shalabh Chaudri, The Ops in MLOps - Process and People, co-hosted by Abi Aryan.
// Abstract
Shalabh talks through their newfound appreciation for the MLOps perspective from a customer success standpoint. Shalabh's emphasis on setting realistic expectations and ensuring the delivery of promised value adds is particularly valuable.
Generally, this episode provides a unique and insightful perspective on MLOps from the lens of customer success.
// Bio
Shalabh has worked in the MLOps domain since 2020 at Algorithmia and Union AI. His experience spans startups and small and large public companies. He has 10+ years of experience in the design, delivery, adoption, and business value realization of B2B infrastructure and platform solutions.
// MLOps Jobs board
jobs.mlops.community
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
https://www.union.ai/
--------------- ✌️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 Abi on LinkedIn: https://www.linkedin.com/in/abiaryan/
Connect with Shalabh on LinkedIn: https://www.linkedin.com/in/shalabhchaudhri/
Timestamps:
[00:00] Shalabh's preferred coffee
[01:18] Takeaways
[02:57] Huge shout-out to Union AI!
[03:46] Reviews
[05:26] Shalab's journey
[07:00] The people and process of MLOps
[10:25] Accuracy measures and Multiple Stakeholders
[13:01] UnionAI's success where others fall short
[14:45] Legacy equipment
[17:06] Legacy tools versus open source
[19:27] Cataloging solution
[22:51] Stakeholders and maturity levels
[24:26] People and Process in MLOps
[29:00] Collaboration for Machine Learning
[31:08] Overcoming challenges
[34:17] AI and leadership decision-making
[35:33] Legacy Companies and AI
[39:39] Common pitfalls
[42:24] Neglecting ROI
[46:25] Speaking to each level
[49:50] Being realistic
[51:29] Becoming a champion
[53:08] Transitioning to machine learning
[55:25] Customer's Skill and Success needed in ML
[57:46] Different sizes of companies
By Demetrios4.6
2323 ratings
MLOps Coffee Sessions #146 with Shalabh Chaudri, The Ops in MLOps - Process and People, co-hosted by Abi Aryan.
// Abstract
Shalabh talks through their newfound appreciation for the MLOps perspective from a customer success standpoint. Shalabh's emphasis on setting realistic expectations and ensuring the delivery of promised value adds is particularly valuable.
Generally, this episode provides a unique and insightful perspective on MLOps from the lens of customer success.
// Bio
Shalabh has worked in the MLOps domain since 2020 at Algorithmia and Union AI. His experience spans startups and small and large public companies. He has 10+ years of experience in the design, delivery, adoption, and business value realization of B2B infrastructure and platform solutions.
// MLOps Jobs board
jobs.mlops.community
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
https://www.union.ai/
--------------- ✌️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 Abi on LinkedIn: https://www.linkedin.com/in/abiaryan/
Connect with Shalabh on LinkedIn: https://www.linkedin.com/in/shalabhchaudhri/
Timestamps:
[00:00] Shalabh's preferred coffee
[01:18] Takeaways
[02:57] Huge shout-out to Union AI!
[03:46] Reviews
[05:26] Shalab's journey
[07:00] The people and process of MLOps
[10:25] Accuracy measures and Multiple Stakeholders
[13:01] UnionAI's success where others fall short
[14:45] Legacy equipment
[17:06] Legacy tools versus open source
[19:27] Cataloging solution
[22:51] Stakeholders and maturity levels
[24:26] People and Process in MLOps
[29:00] Collaboration for Machine Learning
[31:08] Overcoming challenges
[34:17] AI and leadership decision-making
[35:33] Legacy Companies and AI
[39:39] Common pitfalls
[42:24] Neglecting ROI
[46:25] Speaking to each level
[49:50] Being realistic
[51:29] Becoming a champion
[53:08] Transitioning to machine learning
[55:25] Customer's Skill and Success needed in ML
[57:46] Different sizes of companies

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