Systems | Development | Analytics | API | Testing

ClearML

The Clear SHOW - S02E04 - DataOps is All You Need (?)

Can you build your own feature store in two minutes? (sort of) Yes!!! DataOps is all you need. Join Ariel and T.Guerre to find out how! First time hearing about us? Go to - clear.ml! ClearML: One open-source suite of tools that automates preparing, executing, and analyzing machine learning experiments. Bring enterprise-grade data science tools to any ML project.

ClearML hits 1.0

May 3rd 2021 – With over 11 man-years of working, and tinkering, long into the night, I am pleased to announce we have hit version 1.0. Following quickly after the release of ClearML 0.17.5, we added the last remaining features we felt 1.0 needed. Namely multi-model support, as well as improved batch operations. With these in place, the choice was clear. The next version released should be the baseline moving forward.

The Clear SHOW - S02E03 - Your Code == Feature Store

Ariel and T.Guerre discussing the reasoning behind features stores. Should you get one for your production pipeline? First time hearing about us? Go to - clear.ml! ClearML: One open-source suite of tools that automates preparing, executing, and analyzing machine learning experiments. Bring enterprise-grade data science tools to any ML project.

Construction feat. TF2 Object Detection API

Although the title might sound like a collaboration of two music bands with really bad names, this blog is all about understanding how computer vision and machine learning can be used to improve safety and security in a harsh and dangerous environment of a construction site. The construction industry is one of the most dangerous industries according to the common stats from OSHA.

Stacking up against the Competition

One of the most leading questions we often receive is, “How does ClearML Compare to..”. I am sure this is the same for any Open Source product. People always want to find the best. The sad truth is, of course, there usually is no “right answer”. What one person needs, another may not. I am sure that, whichever language you speak natively, there is some saying. In English it would be “one mans rubbish, is another mans gold”.