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  1. Tag "backpropagation"
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10.43K
02:25:52

The spelled-out intro to neural networks and backpropagation: building micrograd

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50:39

#69 DR. THOMAS LUX – Interpolation of Sparse High-Dimensional Data [UNPLUGGED]

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04:54

CoRL 2020, Spotlight Talk 482: Differentiable Logic Layer for Rule Guided Trajectory Prediction

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01:17:08

F18 Lecture 5 : Backpropagation (cont.)

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05:53

Neural Networks Demystified [Part 7: Overfitting, Testing, and Regularization]

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Neural Networks Demystified [Part 6: Training]

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Neural Networks Demystified [Part 5: Numerical Gradient Checking]

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Neural Networks Demystified [Part 4: Backpropagation]

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06:56

Neural Networks Demystified [Part 3: Gradient Descent]

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04:28

Neural Networks Demystified [Part 2: Forward Propagation]

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Neural Networks Demystified [Part 1: Data and Architecture]

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35:05

Pixels to Concepts with Backpropagation w/ Roland Memisevic – #427

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Applications of Deep Neural Networks Class Session 5

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14:07

6.2: Inside Backpropagation Calculation (Module 6, Part 2)

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01:25:43

Lecture 11 Learning in Convolutional Neural Networks

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01:25:15

Lecture 12: Learning in CNNs, transpose Convolution

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01:24:05

Lecture 13: Recurrent Networks

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05:08

Introduction to Neural Networks for C# (Intro)

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04:47

Introduction to Neural Networks for Java (intro)

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18:50

6.1: Backpropagation Introduction for Keras and Tensorflow (Module 6, Part 1)

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09:57

Introduction to Neural Networks for C#(Class 4/16, Part 5/5) – backpropagation

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23:30

Backpropagation, Nesterov Momentum, and ADAM Training (4.4)

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09:54

Introduction to Neural Networks for C#(Class 3/16, Part 5/5)

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10:00

Introduction to Neural Networks for C#(Class 4/16, Part 1/5) – feedforward backpropagation xor

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