In the context of AutoML, describe the detailed steps involved in the machine learning workflow that are typically automated. Discuss how each step contributes to the overall efficiency and effectiveness of the model development process.

Simulated

Data preprocessing, feature selection, model selection, hyperparameter tuning, and model evaluation.

70.3%

Data collection, data cleaning, feature engineering, model training, and model deployment.

14.1%

Data ingestion, data transformation, model training, model validation, and model optimization.

7.8%

Data sampling, feature extraction, model initialization, model testing, and model refinement.

7.8%

Databricks Certified Machine Learning - Associate