lo
Describe automated machine learning
Explain why automated machine learning is different from traditional data science development
Describe the benefits to the organization of adopting automated machine learning
Load and explore data in DataRobot
Build and interpret predictive models using DataRobot
Explain how DataRobot models can be deployed as part of an organization’s operational processes.

The automated machine learning (AML) development process

Import and explore data

Feature lists

Model selection and execution

Constructing the leaderboard

Training, validation, and holdout partitions
best model gets the largest dataset- cost-efficient

Cross-validation
divide training data to 5 partitions, then run 4 partitions as whole respectively , then use the left partition to validate.
downside: 5 passes, for TVH only one. when data scale is large, cross-validation can be prohibited- intensive/ similar results

Autopilot process

Describe, evaluate, and understand models

Variable type processing
Dummy variable coding