Models

Overview

Models are a special type of artifact named model and have a special status in ML Aide since they are the heart of the application.

Example

Experiment 1: Linear Regression

• Run 1: Linear Regression Training 1
  • Artifact 1: Model 1
• Run 2: Linear Regression Training 2
  • Artifact 1: Model 2

Show Models

Instructions

GUI

1. Select the relevant project by clicking it in the home view or via the Projects dropdown in the main navigation
2. Click the Models button in the side navigation

Create Model

Instructions

Code

lin_reg = LinearRegression()
lin_reg.fit(X_train, y_train)

run.log_model(lin_reg, model_name="linear regression model")

Edit Model

Instructions

GUI

1. Select the relevant project by clicking it in the home view or via the Projects dropdown in the main navigation
2. Click the Models button in the side navigation
3. Click the Edit Model button () for the relevant model
4. Change
   • Model stage
   • Note - optional
5. Confirm by clicking the Update button

Show Stage Log

Instructions

GUI

1. Select the relevant project by clicking it in the home view or via the Projects dropdown in the main navigation
2. Click the Models button in the side navigation
3. Click the Stage log button () for the relevant model
4. Close by clicking the Close button