Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software
|
| gptkbp:aims_to |
simplify machine learning process
|
| gptkbp:constructed_in |
gptkb:Keras
|
| gptkbp:developed_by |
gptkb:DATA_Lab,_Texas_A&_M_University
|
| gptkbp:features |
hyperparameter tuning
transfer learning |
| gptkbp:has_community |
gptkb:Stack_Overflow
Git Hub community |
| gptkbp:has_feature |
performance metrics
cloud integration visualization tools cross-validation logging capabilities activation functions early stopping hyperparameter optimization multi-GPU support distributed training optimizers data augmentation techniques ensemble learning batch normalization learning rate scheduling dropout layers model comparison tools model interpretability tools GPU support model checkpointing user-friendly API customizable metrics customizable layers customizable loss functions image augmentation model export options |
| https://www.w3.org/2000/01/rdf-schema#label |
Auto Keras
|
| gptkbp:is_compatible_with |
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch |
| gptkbp:is_used_for |
tabular data
image classification text classification |
| gptkbp:language |
gptkb:Library
|
| gptkbp:license |
Apache License 2.0
|
| gptkbp:provides |
data preprocessing
model selection model evaluation neural architecture search |
| gptkbp:release_date |
gptkb:2018
|
| gptkbp:supports |
deep learning
binary classification regression multi-class classification |
| gptkbp:tutorials |
gptkb:archive
online documentation |
| gptkbp:type |
automated machine learning framework
|
| gptkbp:uses |
gptkb:microprocessor
convolutional neural networks recurrent neural networks |
| gptkbp:bfsParent |
gptkb:Auto_ML
|
| gptkbp:bfsLayer |
4
|