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

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.
ClearML

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.

ClearML

Good Testing Data is All You Need - Guest Post

Building machine learning (ML) and deep learning (DL) models obviously require plenty of data as a training-set and a test-set on which the model is tested against and evaluated. Best practices related to the setup of train-sets and test-sets have evolved in academic circles, however, within the context of applied data science, organizations need to take into consideration a very different set of requirements and goals. Ultimately, any model that a company builds aims to address a business problem.

ClearML

The Train Has Left the Station for the Last Time

We have three big announcements to our community today, and I wanted to talk to you about them: One, Allegro Trains is changing its name, two, we’re adding a completely new way to use Trains, and three, we’re announcing a bunch of features that make Trains an even better product for you! Read all about it on our blog at Clear.ml, our new website for our open source suite of tools.