MLOps project setup: upload ML models to Hopsworks model registry

Here is the previous entry in case you didn't see it. Also this is the code repo for the series and is also updated accordingly.

In this entry these things that are happening:

1. Create a ML model training pipeline
2. Upload the ML model into Hopsworks model registry

Notes on step 1

The model selection is entirely contingent on your data and the objectives within your project, some model examples are: Support Vector Machines (SVM), clustering and neural networks. Right now model serves primarily as a placeholder it's not particularly functional yet. However, the intention is for me to refine it over time creating of more than one version. This just serves as a starting point for the development of my MLOps pipeline.

Notes for step 2

This step detailed breakdown is in this gist lines 43-47:

• get your project's model registry
• create a model in your project's model registry
• push using save() method

Silverboi