Utilizing Zenml to visualize the machine learning pipeline and using standard models as an example. Goal is to better understand the usage of Zenml in the process of training and creating a mode as well as understanding the basic machine learning pipeline.
Splits the pipeline into very basic steps :
- ingesting data
- preprocessing and splitting
- training
- evaluation
Utilizing Zenml makes developing and training a machine learning model more clean as well as giving outputs and a basic roadmap of each pipeline being run. This makes the process of retraining, upgrading, and developing a model much easier and makes understanding how the pipeline works much easier
to open the Zenml dashboard : run : zenml up -blocking this will open up the dashboard locally where the pipeline can be observed