Intuitive Deep Learning Series
23 videos • 2,240 views • by BASIRA Lab
1
[Intuitive Deep Learning] 1.1 Supervised linear and non-linear regression coded in matrices
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2
[Intuitive Deep Learning] 1.2 Supervised linear and nonlinear multiregression coded in matrices
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3
[Intuitive Deep Learning] 1.3 Supervised linear and non-linear classifiers coded in matrices
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[Intuitive Deep Learning] 1.4 Spanning sets & matrix factorization for data representation | PCA
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[Intuitive Deep Learning] 1.5 Spanning sets & matrix factorization for data representation | PCA
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[Intuitive Deep Learning] 1.6 Generalizaed matrix factorization | Multiview data clustering using MF
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7
[Deep Learning Matrix Reloaded] Supervised learning expressed into matrices (part 1)
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8
[Deep Learning Matrix Reloaded] From spanning sets to deep matrix factorization (part 2)
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9
[Intuitive Deep Learning] 2.1 Fully-connected single-layer network coded in matrices
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10
[Intuitive Deep Learning] 2.1 Fully-connected multi-layer network coded in matrices
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11
[Intuitive Deep Learning] 3.1 Activation functions
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12
[Intuitive Deep Learning] 3.2 Gradient Descent & Computation Graphs
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13
[Intuitive Deep Learning] 3.3 Backpropagation: forward and reverse differentiation modes
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14
[Intuitive Deep Learning] 3.4 Batch layer-wise normalization (animated)
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15
[Intuitive Deep Learning] 3.5 Hands-on examples:Shallow to deep nets with backprop and batching
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[Intuitive Deep Learning] 4.1 The logic behind CNNs
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[Intuitive Deep Learning] 4.2 CNNs: invariance | equivariance
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[Intuitive Deep Learning] 4.3 CNNs: invariance | equivariance
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[Intuitive Deep Learning] 4.4 CNNs: Downsampling | upsampling | transposed convolution
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20
[Intuitive Deep Learning] 5.1 Shattered gradients in sequential learning
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21
[Intuitive Deep Learning] 5.2 The logic behind residual connections
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22
[Intuitive Deep Learning] 5.3 Control layer variance with batch normalization
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23
[Intuitive Deep Learning] 5.4 Overview of ResNet, DenseNet and UNet
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