Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
machine learning technique
|
| gptkbp:abbreviation |
gptkb:AutoML
|
| gptkbp:aimsTo |
automate end-to-end process of applying machine learning
|
| gptkbp:challenge |
data privacy
generalization model interpretability computational cost |
| gptkbp:enables |
automated model deployment
automated data transformation automated cross-validation automated data cleaning automated ensembling automated feature selection automated model monitoring automated model retraining automated pipeline creation automated result reporting automated stacking automated validation democratization of AI faster model development reduced human intervention scalability of machine learning |
| gptkbp:field |
gptkb:machine_learning
|
| gptkbp:firstMentioned |
2015s
|
| gptkbp:goal |
make machine learning accessible to non-experts
|
| https://www.w3.org/2000/01/rdf-schema#label |
Automated Machine Learning
|
| gptkbp:includes |
data preprocessing
feature engineering model selection model evaluation hyperparameter optimization |
| gptkbp:relatedTo |
data science
hyperparameter tuning meta-learning neural architecture search |
| gptkbp:usedIn |
gptkb:industry
academia |
| gptkbp:uses |
gptkb:DataRobot
gptkb:RapidMiner gptkb:H2O_AutoML gptkb:Amazon_SageMaker_Autopilot gptkb:Auto-sklearn gptkb:AutoKeras gptkb:MLJAR gptkb:Microsoft_Azure_AutoML gptkb:TPOT gptkb:Google_AutoML |
| gptkbp:bfsParent |
gptkb:AML
|
| gptkbp:bfsLayer |
5
|