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Machine Learning 3 - Generalization K-means | Stanford CS221: AI (Autumn 2019)

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Stanford Online

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

Topics: Generalization, Unsupervised learning, Kmeans
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/percyl...

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

To follow along with the course schedule and syllabus, visit:
https://stanfordcs221.github.io/autu...

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

posted by Ingiosiib