Skip to content

MLOps London November

Photo of
Hosted By
Ed S.
MLOps London November

Details

📽️ Livestream: https://youtu.be/tXZO5x_aVRM
🧑 In Person: https://forms.gle/GWrGXBFwCpKYD6W97
***

MLOps London is back again in November with more talks on production machine learning, DevOps and Data Science. The plan, as usual, is to run another hybrid event so please come along in person if you're local. If you're further afield you will still be able to join the stream.

***

AGENDA:
⏱️ 6.00pm onwards
🍺 Arrival, drinks and networking

⏱️ 6.30pm
🎤 Kick off and welcome

⏱️ 6.40pm
🎤 AI Assurance: Shift-Left and Shift-Right in Machine Learning Systems’ Testing
🧑 Daniel Geater - VP AI Delivery @ Qualitest

It’s no great secret that AI and ML systems make them a challenge for many teams to test. Over the last few years AI infused applications have increased in prominence across sectors and services, a trend that’s set to continue.

As AI & ML infused technology is used more and more and we push for faster and faster delivery, those testing challenges will become more and more apparent and quality assurance teams will need to rise to meet them to preserve velocity or risk massive increases in production issues and reduced system reliability.

Join Qualitest’s Daniel Geater (VP AI Delivery) to find out about how to establish left-shifted and right-shifted quality assurance to enable confident, rapid releases of ML Models by combining automation, Data Science and Quality Engineering best practices.

⏱️ 7.25pm
🎤 Making MLOps Easy and Compliant
🧑 Neven Miculinić - Technical Lead @ Lightning.ai

As an increasing number of industries accelerate their implementation of machine learning tools in production, one significant pain point has been the friction between cloud deployments of those tools and the compliance requirements of a given industry. Verticals with stricter data security requirements, like healthcare and finance, have struggled to implement machine learning tooling that does not yet meet their compliance needs. The ability to remain in control of the data being used to train machine learning models (for example, the ability to use in-house private clusters) is emerging as a key priority for industries seeking to leverage machine learning. In this talk, we’ll explore those pain points in depth, and discuss several emerging solutions that will accelerate the deployment of machine learning solutions in industries with strict security and compliance regulations.

***
If you are attending in person please complete the registration form (link at top of this description)

MLOps London
MLOps London
See more events
41 Luke Street · London