4. Model Creation

At this step, all the requirements have been collected for the solution modelling to proceed.

ML engineers will define the features of the model, taking the following into account:

• Use the same features for training and testing the model to avoid inaccurate results.

Analyse if the KPIs and the business objective of the model are achieved. If the parameters are not met, consider changing the model or improving the quality and quantity of the data.

Before deployment:

• Ensure to measure and monitor the model performance continuously...

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 hyper...