The inaugural MLOps London meetup took place on 28th September – what a way to explode into the London tech community! I was worried at first that MLOps would be too niche of a subject to draw any real interest and I couldn’t have been more wrong. For many attendees, this was their first in-person event for almost 2 years (thanks covid 😒) and there was a real buzz of excitement as people filtered in, grabbed a drink and started networking.
I was conscious that not everyone was ready to meet in person just yet. Others couldn’t make the date or are further afield and weren’t able to travel to London. It was really important to me that these people were still included so, alongside the physical meetup, the event was streamed live to the MLOps London youtube channel.
Running a “hybrid” event is exponentially more difficult than either an in-person or online event. I had to ensure we had good quality audio, video and a clear view of the presenters’ slides on the stream, keep online viewers engaged and respond to their questions, all while running the actual physical event in the room! Thanks to meticulous planning, several test runs and a bit of help from the team at Seldon, things went flawlessly at both ends.
First up was Tatiana Al-Chueyr, a Principal Data Engineer from The BBC. Tatiana gave a fantastic talk about how she, together with a small team of talented data scientists, tackled the challenge of serving recommendations in the BBC Sounds app. Originally outsourced, Tatiana and the team brought the function in-house and managed to deliver a highly performant service at a fraction of the cost whilst increasing user engagement in the app. Her talk covers lots of the hurdles the engineering team faced and the technology components they used along the way. You can view the full talk here.
Our second talk was from the excellent Constantinous Neophytou, VP of Engineering at BenevolentAI. Constantinos’ talk focussed on how the company had built out a centralised Machine Learning platform and practice, allowing individual data science teams to spend less time building infrastructure and more time tackling business problems. The talk is a great example of how an organisation can define best practices from across their engineering function. Make sure you check out some of the really interesting questions Constantinos answers after his presentation.
It was awesome to see that, after the talks had ended, lots of people stuck around to share their own experiences and network with other MLOps enthusiasts. The discussion continued even after the venue had booted us out and we’d decamped to the pub where we even played pool (of varying quality 😊).
Our next event is on 23rd November where Nick Masca, Head of Data Science at Marks and Spencer will be talking about their MLOps journey. Details and signup can be found here.
Ed comes from a cloud computing background and is a strong believer in making deployments as easy as possible for developers. With an education in computational modelling and an enthusiasm for machine learning, Ed has blended his work in ML and cloud native computing together to cement himself firmly in the emerging field of MLOps. Organiser of Tech Ethics London and MLOps London, Ed is heavily involved in lots of developer communities and, thankfully, loves both beer and pizza.