Models

Saving & loading a Data Science Lab model

Check-out the walk-through on how to save and load a DSL Model.

Saving and loading a model

Once the Notebook script is executed successfully, the users can save them as a model. The saved model can be loaded into the Notebook.

Saving a Data Science Lab Model

• Navigate to a Notebook.

• Write code using the following sequence:

  • Read DataFrame

  • Define test and train data

  • Create a model

• Execute the script.

Sample Script for a Data Science Model

• Get a new cell.

• Give a model name to specify the model.

• Execute the cell.

• After the code gets executed, click the Save Model notebook in a new cell.

• The saved model gets listed under the Models list.

Function Parameters

• Model - Trained model variable name.

• ModelName - Desired name given by user for the trained model.

• ModelType - Type in which model can be saved.

• X - This array contains the input features or predictors used to train the model. Each row in the X_train array represents a sample or observation in the training set, and each column represents a feature or variable.

• y - This array contains the corresponding output or response variable for each sample in the training set. It is also called the target variable, dependent variable, or label. The y_train array has the same number of rows as the X_train array.

• estimator_type - The estimator_type of a data science model refers to the type of estimator use.

Specify a Data Science Lab Model by giving a name

Loading a Data Science Lab Model

• Click on a new cell and select the model by using the given checkbox to load it.

• The model gets loaded into a new cell.

Loading a saved Data Science Lab Model

Please Note: Refer the Data Science Lab Quick Start Flow page to get an overview of the Data Science Lab module in nutshell. Click here to get redirected to the quick start flow page.