The Shallow and the Deep (Record no. 39652)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02837nam a2200373 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | OTLid0001516 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | MnU |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20241120064034.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION | |
| fixed length control field | m o d s |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 231021s2023 mnu o 0 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789403430270 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | MnU |
| Language of cataloging | eng |
| Transcribing agency | MnU |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA76 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Biehl, Michael |
| Relator term | author |
| 245 04 - TITLE STATEMENT | |
| Title | The Shallow and the Deep |
| Remainder of title | A biased introduction to neural networks and old school machine learning |
| Statement of responsibility, etc | Michael Biehl |
| 264 #2 - | |
| -- | Minneapolis, MN |
| -- | Open Textbook Library |
| 264 #1 - | |
| -- | Groningen, Netherlands |
| -- | University of Groningen Press |
| -- | 2023. |
| 264 #4 - | |
| -- | ©2023. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 490 0# - SERIES STATEMENT | |
| Series statement | Open textbook library. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Preface -- From neurons to networks -- Learning from example data -- The Perceptron -- Beyond linear separability -- Feed-forward networks for regression and classification -- Distance-based classifiers -- Model evaluation and regularization -- Preprocessing and unsupervised learning -- Concluding quote -- Appendix A: Optimization -- List of figures -- List of algorithms -- Abbrev. and acronyms -- Bibliography |
| 520 0# - SUMMARY, ETC. | |
| Summary, etc | The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon. Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility. |
| 542 1# - | |
| -- | Attribution-NonCommercial-ShareAlike |
| 546 ## - LANGUAGE NOTE | |
| Language note | In English. |
| 588 0# - | |
| -- | Description based on online resource |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Science |
| Form subdivision | Textbooks |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence |
| Form subdivision | Textbooks |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Open Textbook Library |
| Relator term | distributor |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://open.umn.edu/opentextbooks/textbooks/1516">https://open.umn.edu/opentextbooks/textbooks/1516</a> |
| Public note | Access online version |
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