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gptkbp:instanceOf
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gptkb:convolutional_neural_network
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gptkbp:abbreviation
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gptkb:MLP
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gptkbp:alternativeTo
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gptkb:Radial_Basis_Function_Network
gptkb:convolutional_neural_network
gptkb:Recurrent_Neural_Network
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gptkbp:developedBy
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1970s
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gptkbp:hasActivationFunction
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gptkb:ReLU
gptkb:Sigmoid
gptkb:Tanh
Softmax
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gptkbp:hasApplication
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gptkb:Speech_Recognition
Medical Diagnosis
Image Recognition
Financial Forecasting
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gptkbp:hasComponent
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Hidden Layer
Input Layer
Output Layer
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gptkbp:hasLossFunction
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gptkb:Mean_Squared_Error
Cross-Entropy Loss
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gptkbp:hasProperty
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Feedforward Architecture
Fully Connected Layers
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gptkbp:hasRegularization
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gptkb:Dropout
L2 Regularization
L1 Regularization
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gptkbp:hasTrainingAlgorithm
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Stochastic Gradient Descent
Batch Gradient Descent
Mini-batch Gradient Descent
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https://www.w3.org/2000/01/rdf-schema#label
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Multi-layer Perceptron
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gptkbp:inventedBy
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gptkb:Frank_Rosenblatt
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gptkbp:limitation
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Requires Large Datasets
Prone to Overfitting
Cannot Handle Variable-Length Input
Cannot Model Sequential Data
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gptkbp:parameter
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Weights
Learning Rate
Biases
Number of Layers
Number of Neurons
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gptkbp:relatedTo
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gptkb:Machine_Learning
gptkb:artificial_intelligence
gptkb:Perceptron
Deep Learning
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gptkbp:trainer
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Gradient Descent
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gptkbp:usedIn
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Regression
Classification
Supervised Learning
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gptkbp:uses
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Activation Function
Backpropagation
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gptkbp:bfsParent
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gptkb:Adaptive_Linear_Neuron
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gptkbp:bfsLayer
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8
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