D2L
D2L 6.6 LeNet
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Computer Science
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D2L 6.5 Pooling Layer
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D2L 6. ConvolutionNeuronNetwork
D2L
D2L 6.4 Multiple Input & Output
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Computer Science
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D2L 6.3 Padding & Stride
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D2L 6.2 Image Convolution
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D2L 5.4 Custom Layer
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D2L 5. Deep Learning Computation
D2L
D2L 5.3 Deferred Initialization
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Computer Science
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D2L 5.2 Parameter Management
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Computer Science
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D2 5.1 Layer & Block
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D2L 4.2 Example of MLP
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D2L 4.1 Multilayer Perceptron
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D2L Weierstrass Approximation Theorem
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Computer Science
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Linear Regression
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Computer Science
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D2L 4.4 Model Selection, Underfitting, and Overfitting
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D2L 4.1 MultilayerPerceptron
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D2L 3.6 Implementation of softmax regression from scratch
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D2L 3.5 Image classification datasets
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D2L 3.4 Softmax Regression
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D2L 3.3 A concise implementation of linear regression
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D2L 3.2 Object-Oriented Design for Implementation
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D2L 3.1 Linear Regression
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Dive Into Deep Learning
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Computer Science
Cover
Chapter 4. Multilayer Perceptron
D2L
Chapter 3. Linear Neural Network
D2L