Versioning Machine Learning Experiments vs Tracking Them

When working on a machine learning project it is common to run numerous experiments in search of a combination of an algorithm, parameters and data preprocessing steps that would yield the best model for the task at hand. To keep track of these experiments Data Scientists used to log them into Excel sheets due to a lack of a better option. However, being mostly manual, this approach had its downsides. To name a few, it was error-prone, inconvenient, slow, and completely detached from the actual experiments. Luckily, over the last few years experiment tracking has come a long way and we have seen a number of tools appear on the market that improve the way experiments can be tracked, e.g.