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Anatomy of a Learning Problem
Published on Jan 25, 20124259 Views
In order to relate machine learning problems we argue that we need to be able to articulate what is meant by a single machine learning problem. By attempting to name the various aspects of a learning
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Chapter list
Anatomy of a Learning Problem00:00
Relations Between Problems - 101:01
Relations Between Problems - 201:38
The Diseasome Map - 101:52
The Diseasome Map - 203:13
MLComp Website03:30
How can we organise a zoo?04:20
From Folk to Scientific Taxonomy - 105:20
From Folk to Scientific Taxonomy - 205:31
From Folk to Scientific Taxonomy - 305:55
From Folk to Scientific Taxonomy - 407:01
From Folk to Scientific Taxonomy - 507:41
George Boole08:02
What’s been done?08:27
What does it mean to learn? - 108:45
What does it mean to learn? - 209:13
The UCI Repository - 109:55
The UCI Repository - 210:06
The UCI Repository - 310:30
The UCI Repository - 410:51
The UCI Repository - 510:59
ML Data - 111:27
ML Data - 211:48
ML Data - 311:56
ML Data - 412:02
ML Data - 512:10
ML Data - 612:17
ML Comp - 112:44
ML Comp - 213:01
ML Comp - 313:21
ML Comp - 413:43
ML Comp - 514:04
A Prescription - 114:19
A Prescription - 214:54
A Prescription - 315:18
Genus-Differentia Definitions - 115:22
Genus-Differentia Definitions - 216:03
Genus-Differentia Definitions - 316:06
Genus-Differentia Definitions - 416:22
Genus-Differentia Definitions - 516:26
Genus-Differentia Definitions - 616:57
Genus-Differentia Definitions - 717:07
Genus-Differentia Definitions - 817:11
Genus-Differentia Definitions - 917:22
Data - Models/Predictions - Assessment - 117:56
Data - Models/Predictions - Assessment - 218:20
Data - Models/Predictions - Assessment - 318:39
Data - Models/Predictions - Assessment - 418:49
Data - Models/Predictions - Assessment - 519:03
Data - Models/Predictions - Assessment - 619:13
Data - Models/Predictions - Assessment - 719:21
Data - Models/Predictions - Assessment - 819:50
Data - Models/Predictions - Assessment - 923:22
Data - Models/Predictions - Assessment - 1023:37
Data - Models/Predictions - Assessment - 1123:46
Perspectives through Taxonomy - 124:07
Perspectives through Taxonomy - 224:30
Perspectives through Taxonomy - 324:51
Perspectives through Taxonomy - 425:02
Perspectives through Taxonomy - 525:09
Conclusions?25:34
Thanks26:11