Versioning and storing your model
As we have been working through this book, there has been one glaring issue that you might have noticed – when you closed your integration development environment, terminal, or Jupyter notebook, your model and data were gone. We won't go into the more involved topics of working and saving information on databases or other persistence layers, but there are some quite simple things you can do to create save points along the way.
Understanding the value of versioning your model
As you've worked through everything from data engineering to building models in this book, you have realized that there are a lot of iterations that happen. It's called data science, but there is also an art to guessing a path and trying to know where to go next. You've tried to make educated guesses with hyperparameters and model families, and kept the original dataset open to come back to as needed. This was all needed in case you were wrong....
