Controlling the norm: early stopping(00:24:21 - 00:27:34) - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Controlling the norm: early stopping(00:24:21 - 00:27:34)
Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/30Z6b0p

Topics: Generalization, Unsupervised learning, K-means
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor - Stanford University
http://online...
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/30Z6b0p

Topics: Generalization, Unsupervised learning, K-means
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor - Stanford University
http://onlinehub.stanford.edu/

Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
https://profiles.stanford.edu/percy-liang

Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
https://profiles.stanford.edu/dorsa-sadigh

To follow along with the course schedule and syllabus, visit:
https://stanford-cs221.github.io/autumn2019/#schedule

0:00 Introduction
0:34 Review: feature extractor
0:53 Review: prediction score
1:18 Review: loss function
3:42 Roadmap Generalization
3:58 Training error
4:26 A strawman algorithm
5:15 Overfitting pictures
5:51 Evaluation
9:20 Approximation and estimation error
11:27 Effect of hypothesis class size
12:51 Strategy 1: dimensionality
13:34 Controlling the dimensionality
14:21 Strategy: norm
24:21 Controlling the norm: early stopping
27:34 Hyperparameters
30:22 Validation
36:18 Development cycle
55:08 Supervision?
58:12 Word vectors
58:58 Clustering with deep embeddings
Introduction - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Introduction

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:00:00 - 00:00:34
Review: feature extractor - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Review: feature extractor

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:00:34 - 00:00:53
Review: prediction score - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Review: prediction score

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:00:53 - 00:01:18
Review: loss function - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Review: loss function

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:01:18 - 00:03:42
Roadmap Generalization - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Roadmap Generalization

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:03:42 - 00:03:58
Training error - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Training error

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:03:58 - 00:04:26
A strawman algorithm - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

A strawman algorithm

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:04:26 - 00:05:15
Overfitting pictures - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Overfitting pictures

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:05:15 - 00:05:51
Evaluation - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Evaluation

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:05:51 - 00:09:20
Approximation and estimation error - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Approximation and estimation error

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:09:20 - 00:11:27
Effect of hypothesis class size - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Effect of hypothesis class size

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:11:27 - 00:12:51
Strategy 1: dimensionality - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Strategy 1: dimensionality

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:12:51 - 00:13:34
Controlling the dimensionality - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Controlling the dimensionality

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:13:34 - 00:14:21
Strategy: norm - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Strategy: norm

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:14:21 - 00:24:21
Controlling the norm: early stopping - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Controlling the norm: early stopping

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:24:21 - 00:27:34
Hyperparameters - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Hyperparameters

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:27:34 - 00:30:22
Validation - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Validation

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:30:22 - 00:36:18
Development cycle - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Development cycle

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:36:18 - 00:55:08
Supervision? - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Supervision?

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:55:08 - 00:58:12
Word vectors - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Word vectors

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:58:12 - 00:58:58
Clustering with deep embeddings - Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)

Clustering with deep embeddings

Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
2020年01月09日 
00:58:58 - 01:23:07

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