A hands-on tutorials in  big/ML experiment management.

The purpose of this tutorial is to introduce students to how to manage machine learning experiments using MLFlow. This will consist of how to reproduce, track, and evaluate your experiments. Within an experiment, we will capture relationships among configurable parameters, machine learning code, the input data, output result, and performance metrics. In addition, we can also check the reproducibility of a machine learning algorithm.

To have an overview of the tutorial, the student can take a look at the tutorial link:

      https://version.aalto.fi/gitlab/sys4bigml/cs-e4660/-/tree/master/tutorials%2FMLProjectManagement

It is recommended that students will install the required software so that we can go smoothly with the tutorial. For instance, students could install conda, python and sklearn library. However, it is not mandatory, we can do it together in the tutorial.

Last modified: Friday, 5 February 2021, 6:01 PM