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ClearML

How to Use a Continual Learning Pipeline to Maintain High Performances of an AI Model in Production - Guest Blogpost

The algorithm team at WSC Sports faced a challenge. How could our computer vision model, that is working in a dynamic environment, maintain high quality results? Especially as in our case, new data may appear daily and be visually different from the already trained data. Bit of a head-scratcher right? Well, we’ve developed a system that is doing just that and showing exceptional results!

Improving a day in the life of: Data Scientist - How ClearML is actually used.

ClearML in the real world, without the marketing fluff. Watch along as we show how ClearML integrates with this audio classification use case. Get lots of tips, tricks and inspiration on the use of the experiment manager and remote agents for use in your own day-to-day life as a data scientist. Chapters.

Cloud vendor's MLOps or Open source?

If someone had told my 15-years-ago self that I’d become a DevOps engineer, I’d have scratched my head and asked them to repeat that. Back then, of course, applications were either maintained on a dedicated server or (sigh!) installed on end-user machines with little control or flexibility. Today, these paradigms are essentially obsolete; cloud computing is ubiquitous and successful.