Setting up MLflow

MLflow is an open source tool that is primarily written in Python. It has over 10,000 stars tagged in its GitHub source repository (https://github.com/mlflow/mlflow). The benefits of using MLflow are numerous, but we can illustrate one benefit with the following scenario: Let's say you are starting a new ML project, trying to evaluate different algorithms and model parameters. Within a few days, you run hundreds of experiments with lots of code changes using different ML/DL libraries and get different models with different parameters and accuracies. You need to compare which model works better and also allow your team members to reproduce the results for model review purposes. Do you prepare a spreadsheet and write down the model name, parameters, accuracies, and location of the models? How can someone else rerun your code or use your trained model with a different set of evaluation datasets? This can quickly become unmanageable when you have lots of iterations...