Building Trust in Machine Learning with Business Stakeholders
Chris Lacava
VP of Product
Machine learning is often received with skepticism by business stakeholders. How can ML be presented in a way that non-data scientist stakeholders can assess it's output objectively and build confidence in it's application? We'll review techniques, pit falls and examples of creating model comparison analysis solutions for business use cases that take a hybrid approach. We'll explore ways that ML can live alongside established analytics processes harmoniously along with other strategies that foster adoption of ML among business stakeholders. Chris LaCava, VP of Product, Expero - Recorded for the online CTO Summit on Tuesday July 13th, 2021 on building a data science team -
Interested in Structuring?
Visit our Structuring community!
How should an ideal organization look like? What approaches can help you to make your organization more efficient? Let's try to find answers together in our Structuring community. Here we discuss topics of org design/team structure, process (agile/kanban, etc), engineering metrics, knowledge management/documentation.
Bryan Helmkamp, Founder and CEO at Code Climate
Brian guthrie, Co-Founder and CTO at Orgspace
Mona Soni, CTO at Sustainable1 at S&P
Denise Iglesias, EVP, Product and Engineering at Dealerware
Randy Shoup, VP Engineering and Chief Architect at eBay
Johanna Rothman, Owner at Rothman Consulting Group
Liz Keogh, Lean/agile consultant at Lunivore
Ashkan Roshanayi, Founder at DataChef - Ex Amazonian at DataChef
Neville Samuell, VP of Engineering at Ethyca
Alex Maher, Talent Partner | DE&I Lead at Artium
Emily Nakashima, VP Engineering at
Colleen Tartow, Director of Engineering at Starburst Data

Copyright © 2022 CTO Connection, All Rights Reserved