[Day 184] Mlflow experiment tracking and trying out metaflow
Hello :) Today is Day 184! A quick summary of today: got various experiments ran and saved in my GCP mlflow server set up and tried out metaflow for MLOps orchestration Today I had to re-create my GCP VM because of a python version issue. So after starting a VM with python 3.10 I could use mlflow's most current logging functionality. I ran a few experiements and the currently saved are: I will select a model solely based on recall - being able to detect the most fraud cases out of all fraud cases. Based on that, so far (after finding optimal params) the Balanced RF Classifier is the best -> recall being 0.92. The most recent code and files are in my repo . Today I did some refactoring to make things look nicer -> added a utils folder with some helper functions that I used a lot throughout notebooks. The current are log_model_performance and get_best_params which log a model run to mlflow, and then load the params of a model from mlflow. Another thing - I asked on reddit&