The Challenges of Machine Learning Deployment - Veselina Staneva
Date and time
Location
Online event
Join this talk to learn about growing a product mindset in MLOps, the challenges around deployments, delivering business value, and more
About this event
We'll be speaking with Veselina Staneva about how to grow a product mindset in MLOps, the challenges around deployments, delivering business value, speed of iteration, and how increasing it is mission critical.
About the Guest:
Our guest for this talk is Veselina Staneva, Co-founder & Head of Product at TeachableHub.
Over the past few years, Vesi has worked at the product company CloudStrap.io, where her team is simplifying cloud technologies and crafting modern solutions that lay a solid foundation for digital transformation at scale. Vesi's main focus currently is their latest product www.TeachableHub.com - an ML deployment and serving platform for product teams, where she heads Product and Customer Development.
In her free time, she enjoys spending the rest of her energy doing all kinds of sports and hiking with her family.
Deploy your models in minutes by signing up for free TeachableHub early access or connect with Vesi to chat about ML deployment challenges and book a TeachableHub demo.
TeachableHub early access: https://www.teachablehub.com/#early-access
Connect with Vesi on LinkedIn: https://www.linkedin.com/in/veselina-d-staneva/
About Robust & Responsible (Rsqrd) AI:
Rsqrd AI is a community of AI builders [engineers, scientists, product managers, etc] who are committed to making AI technology robust & responsible. We regularly organize community events to share knowledge and collaborate on best practices for enterprise-scale AI development.
This group is managed by the wonderful people at https://whylabs.ai - Enable AI Observability to achieve healthy models, fewer incidents, and happy customers.
Join the Rsqrd community Slack: https://bit.ly/rsqrd-slack
Sign-up to speak at an event: https://bit.ly/rsqrd-speak
Try our open-source data logging project: https://github.com/whylabs/whylogs