CS 152 NN—6: Regularization—Neural-network-specific

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Day 6 of Harvey Mudd College Neural Networks class
  1. Neil Rhodes
  2. Neural Networks
  3. Deep Learning
  4. HMC
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CS 152 NN—6: 0:00:57

CS 152 NN—6: Regularization—Neural-network-specific

CS 152 NN—6: 0:09:42

CS 152 NN—6: Regularization

CS 152 NN—6: 0:14:00

CS 152 NN—6: Regularization—Data Augmentatipon

CS 152 NN—6: 0:04:49

CS 152 NN—6: Regularization—Multi-task Learning

CS 152 NN—6: 0:10:24

CS 152 NN—6: Regularization—Ensembles

CS 152 NN—6: 0:09:56

CS 152 NN—6: Regularization—Adjust Loss Function

CS 152 NN—6: 0:05:34

CS 152 NN—6: Regularization—Mixup

CS 152 NN—6: 0:02:24

CS 152 NN—6: Regularization—Early stopping

CS 152 NN—6: 0:02:30

CS 152 NN—6: Regularization—Larger learning rate

CS 152 NN—6: 0:01:21

CS 152 NN—6: Regularization—Smaller batches

CS 152 NN—6: 0:06:36

CS 152 NN—6: Regularization—Noise Injection

CS 152 NN—16: 0:06:46

CS 152 NN—16: Multi task Learning

CS 152 NN—12: 0:19:10

CS 152 NN—12: Regularization: Batch Normalization

CS 152 NN—9: 0:09:00

CS 152 NN—9: Neural Networks—Visualizing the network

CS 152 NN—8: 0:04:38

CS 152 NN—8: Regularization—Label Smoothing

CS 152 NN—5: 0:15:04

CS 152 NN—5: Normalization

CS 152 NN—8: 0:02:17

CS 152 NN—8: Optimizers—Weight decay

CS 152 NN—13: 0:18:17

CS 152 NN—13: Convolutions: 3 dimensions

CS 152 NN—7: 0:08:35

CS 152 NN—7: Binary Classification —Sigmoid

CS 152 NN—8: 0:08:17

CS 152 NN—8: Multi-category classification

CS 152 NN—2: 0:18:47

CS 152 NN—2: Overfitting-Underfitting

CS 152—Lecture 02 1:14:54

CS 152—Lecture 02 (HMC Fall, 2018)

CS 152 NN—2: 0:08:13

CS 152 NN—2: Intro to ML—Low validation loss, high training loss

I2ML - Regularization 0:23:34

I2ML - Regularization - Nonlinear & Bayesian Regularization