Librarian View
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991001662809707546
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20220623132729.0
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210928s2012 enka b 001 0 eng d
010
a| 2012289353
015
a| GBB254843
2| bnb
020
a| 9781107422223
q| (Paperback)
020
z| 9781107096394
q| (Hardback)
035
a| (HKSYU)b21407654-852hksyu_inst
035
a| (OCoLC)795181906
040
a| UKMGB
b| eng
e| rda
c| UKMGB
d| BTCTA
d| OCLCO
d| BDX
d| YDXCP
d| CDX
d| ZWZ
d| EYM
d| TEF
d| JHE
d| MUU
d| DLC
d| VRC
d| OCLCF
d| HK-SYU
050
4
a| Q325.5
b| .F5 2012
092
0
a| 006.31
b| FLA 2012
100
1
a| Flach, Peter A,
e| author.
245
1
0
a| Machine learning :
b| the art and science of algorithms that make sense of data /
c| Peter Flach
246
3
0
a| Art and science of algorithms that make sense of data
264
1
a| Cambridge ;
a| New York :
b| Cambridge University Press,
c| 2012
264
4
c| ©2012
300
a| xvii, 396 pages :
b| illustrations ;
c| 25 cm
336
a| text
b| txt
2| rdacontent
337
a| unmediated
b| n
2| rdamedia
338
a| volume
b| nc
2| rdacarrier
504
a| Includes bibliographical references (pages 367-381) and index
505
0
a| 1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here
520
3
a| 'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike
650
0
a| Machine learning
v| Textbooks.
907
a| b21407654
b| 08-01-22
c| 28-09-21
910
a| ykc
b| mkl
935
a| (HK-SYU)501036269
9| ExL
998
a| book
b| 29-10-21
c| m
d| a
e| -
f| eng
g| enk
h| 0
i| 0
945
h| Supplement
l| location
i| barcode
y| id
f| bookplate
a| callnoa
b| callnob
n| ADS410