When I launched the MLOps London Meetup in September 2021, I figured if I could get 10 or 15 people together to talk about production ML that would be a win. My expectations were completely surpassed and continue to be every time.
Tuesday 29th November saw the MLOps community gather for our final meetup of 2022, one that clashed with England playing Wales in the football world cup. Whilst this might have deterred a few, the attendance was incredibly strong and the conversations that flowed during the networking were fantastic.
Our first speaker was Daniel Geater, VP AI Delivery at Qualitest. He spoke at length about his experiences doing testing on ML projects and how we can reuse the testing frameworks from software development to “shift left” the testing and carry out as much as possible during the early phases of our ML lifecycle. I particularly liked his mapping of machine learning testing/validation techniques to the software testing pyramid:
You can catch the recording of Daniel’s talk here.
Next up was Neven Miculinić, experienced software and machine learning engineer. Neven had originally planned to talk about a framework he worked on but, having moved on from his previous employer, realized it gave him the freedom to talk openly about experiences he’s had throughout his engineering career.
His talk covered from birth right up to now and highlighted the different books and resources he’d found useful along the way. He also pointed out some of the horrible experiences he’d had such as long release cycles with fixed delivery dates and the mess you can get into if you don’t do trunk-based development. It was a refreshing personal perspective on the engineering industry and definitely gave us all some things to think about going into the Christmas break. You can catch Neven’s full talk here.
Speaking of which, this was the last event in 2022. We’ll be back on the 10th January so keep an eye on the meetup page and subscribe to the YouTube channel for updates. Until then, have a very merry Christmas and a happy new year.
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.