The ML workflow - Deepstash

The ML workflow

The ML workflow

The ML workflow

To develop and manage a production-ready model, you must work through the following stages:

  • Source and prepare your data.
  • Develop your model.
  • Train an ML model on your data:

  • Train model

  • Evaluate model accuracy
  • Tune hyperparameters

  • Deploy your trained model.

  • Send prediction requests to your model:

  • Online prediction

  • Batch prediction

  • Monitor the predictions on an ongoing basis.

  • Manage your models and model versions.

These stages are iterative. You may need to reevaluate and go back to a previous step at any point in the process.

44

122 reads

It's time to

READ

LIKE

A PRO!

Jump-start your

reading habits

, gather your

knowledge

,

remember what you read

and stay ahead of the crowd!

It takes just 5 minutes a day.


TRY THE DEEPSTASH APP

+2M Installs

4.7 App Score