Our 1st MLOps Meetup // Luke Marsden // MLOps Meetup #1

The 1st MLOps.community meetup on 3.18.2020 featuring Luke Marsden from Dotscience.

What is MLOps and how can it help me work remotely? The first episode of our weekly MLOps community virtual meetup with CEO and founder of the MLOps platform dotscience Luke Marsden talk to us about the current state of Machine Learning, what some of the main difficulties are at this stage when developing models, how the machine learning lifecycle differs from traditional software development and a deep dive of collaboration for data science teams in a fully remote world.

MLOps is the intersection of three disciplines: software engineering, DevOps and machine learning. MLOps refers to the entire end-to-end lifecycle of getting models from lab to live where they can start delivering value.

What do software engineers and DevOps need to learn about machine learning to ensure that it can be integrated into their dev & deployment pipelines? What do data scientists and ML engineers need to learn about DevOps, model deployment and monitoring to ensure they can effectively deploy their work without racking up tonnes of technical debt? And now that working from home is fast becoming the new normal, how can MLOps help my team stay efficient when asynchronous collaboration is needed, something our software engineering and DevOps friends have already mastered?

MLOps is a complex discipline due to the many more moving parts involved than regular software DevOps, in this inaugural MLOps.community meetup we'll explore and navigate this new space together and give you a guide on how to avoid the most common pitfalls and challenges getting AI into production and collaborating effectively with your team – even when you're distributed.

Join our open community where we discuss everything MLOps: https://mlops.community/
Join our MLOps slack channel: https://bit.ly/33wDUf1
MLOps.community forums: https://forum.mlops.community/
Sign up for the next weekly meetup: https://zoom.us/webinar/register/WN_a_nuYR1xT86TGIB2wp9B1g

Episode source