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In this episode, Michelle Carney, a Senior UX Researcher on Google’s TensorFlow team, joins Hugo Bowne-Anderson to discuss how combining ML and user experience (UX) creates more impactful products. Michelle shares why UX should be a top consideration for data scientists and ML practitioners and offers practical guidance on designing ML products that truly resonate with users.
As part of our newly launched podcast, we’re converting previous Fireside Chats into podcast episodes because the lesson are still incredibly valuable today. Once we catch up with these past discussions, we’ll continue releasing new and fresh content to keep you at the forefront of ML Engineering.
Key takeaways:
- Why data scientists need to start thinking about UX
- The top things data professionals should know about UX design to improve their ML products
- How to measure the success of UX initiatives for ML
- How UX design connects to other ML aspects like usability, explainability, and ethics
Outerbounds empowers organizations with a scalable, human-centric ML platform to unlock the full potential of machine learning. Learn more at Outerbounds.com.
Stay tuned as we continue releasing both past and new content to help guide you on your ML Engineering journey!
