Deepchecks’ ML Team Lead Noam Bressler spoke alongside Magdalena Konkiewicz (Data Evangelist @ Toloka Ai) and Moses Gutmann (CEO @ ClearML) about building a solid foundation for MLOps.
Every piece of traditional software goes through comprehensive tests of various types before deployment, and is continuously monitored in production. How can we adapt these ideas to the data-oriented world of ML? We’ll discuss best practices for extensively testing and analyzing computer vision data and models with Deepchecks. Using the open source package, we’ll show how to detect errors in your data, model, and methodology both before an ML product is released and throughout its production lifecycle.
Here is Noam’s talk for those who weren’t able to attend the Tel-Aviv event.
