Deep Learning336 Videos

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6
01:24:05

Lecture 13: Recurrent Networks

00:00 Introduction 00:14:55 Finite Response Model 00:23:00 Infinite Response System 00:30:00 NARX Network 00:34:30 Jordan Network 00:35:50 Elman Network 00:43:00 State Space Model 00:51:30 Recurrent Neural Network 00:59:10 Variants 01:04:30 Training the RNN 01:10:50 Backpropagation through RNN YouTube Source for this AI Video
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01:22:38

Lecture 10 | CNNs pt 2

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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4
05:46

Recitation 0d | Dataset and Data Loaders

Python Notebook: https://colab.research.google.com/drive/1B7txmVhPfNPjI_QkqNDLm2x62JivmdSn?usp=sharing Reference Link: https://libraries.io/github/deepology/ideel-tutorials For more information, please visit: http://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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11
01:25:02

Lecture 8 | Normalization, Regularization etc.

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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2
57:25

Recitation 8p2 | Listen Attend Spell

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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5
01:37:08

Lecture 16 | CTC and seq2seq

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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5
01:01:42

Recitation 4 | Debugging and Visualization

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Debugging tools • Optimization techniques • Visualization • Neural network sanity checks YouTube Source for this AI Video
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4
53:08

Recitation 7 | CTC

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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11
50:18

Lecture 5: Part 2

00:00 Vector formulation 00:06:41 Forward Pass 00:13:19 Vector Calculus 00:30:26 Backward Pass 00:46:11 Digit Recognition YouTube Source for this AI Video
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12
01:17:14

(Old) Recitation 4 | Debugging and Visualization

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Spring 2019 Materials: https://github.com/cmudeeplearning11785/Spring2019_Tutorials/tree/master/recitation-4 For more information, please visit: http://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video
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6
01:48:02

Lecture 21 | VAEs

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2020 For more information, please visit: https://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video