Statements (58)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Company
|
| gptkbp:brewingProcess |
Forward Propagation
|
| gptkbp:canBe |
Batch Normalization
Gradient Descent Dropout Regularization |
| gptkbp:canLeadTo |
Training Data
|
| gptkbp:hasArtStyle |
Layered Structure
|
| https://www.w3.org/2000/01/rdf-schema#label |
Feedforward Neural Network
|
| gptkbp:isCharacterizedBy |
No Cycles
Deterministic Outputs Fixed Architecture Feedforward_Connections |
| gptkbp:isComposedOf |
Output Layer
Hidden Layers Input_Layer |
| gptkbp:isEvaluatedBy |
Accuracy
F1 Score Precision Recall Loss Function Confusion Matrix ROC_Curve AUC Score |
| gptkbp:isInfluencedBy |
gptkb:Biological_Neural_Networks
Cognitive Science Mathematics Statistics |
| gptkbp:isInvolvedIn |
gptkb:PyTorch
gptkb:Keras Python TensorFlow |
| gptkbp:isPopularIn |
Deep Learning
|
| gptkbp:isRelatedTo |
gptkb:Convolutional_Neural_Network
Recurrent Neural Network |
| gptkbp:isTestedFor |
Backpropagation
|
| gptkbp:isUsedBy |
gptkb:Recommendation_Systems
Anomaly Detection Image Recognition Medical Diagnosis Natural Language Processing Speech Recognition Time Series Prediction Game AI Financial Forecasting |
| gptkbp:isUsedFor |
Classification
Regression Early Stopping Learning Rate Adjustment Neural Network Diagrams Model Ensembling Hyperparameter_Tuning |
| gptkbp:isUsedIn |
Supervised Learning
|
| gptkbp:isVisitedBy |
gptkb:Geoffrey_Hinton
gptkb:Yoshua_Bengio gptkb:Yann_LeCun Vanishing Gradient Problem |
| gptkbp:providesTrainingFor |
Labeled Data
|
| gptkbp:utilizes |
Non-linear Functions
|