Mathematics and R programming for machine learning : (Record no. 130712)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04415cam a22005771i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9781003051220 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FlBoTFG |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220509193135.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION | |
| fixed length control field | m d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr ||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200818t20202021flua ob 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | OCoLC-P |
| Language of cataloging | eng |
| Description conventions | rda |
| -- | pn |
| Transcribing agency | OCoLC-P |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000196993 |
| -- | (ePub ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1000196992 |
| -- | (ePub ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000196979 |
| -- | (PDF ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1000196976 |
| -- | (PDF ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000196986 |
| -- | (Mobipocket ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1000196984 |
| -- | (Mobipocket ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781003051220 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1003051227 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Cancelled/invalid ISBN | 9780367561949 (hbk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Cancelled/invalid ISBN | 9780367507855 (pbk.) |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1201/9781003051220 |
| Source of number or code | doi |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC)1198598560 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC-P)1198598560 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q325.5 |
| Item number | .C53 2020eb |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM |
| Subject category code subdivision | 004000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM |
| Subject category code subdivision | 051300 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM |
| Subject category code subdivision | 051210 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UY |
| Source | bicssc |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Claster, William B., |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | Mathematics and R programming for machine learning : |
| Remainder of title | from the ground up / |
| Statement of responsibility, etc | William B. Claster. |
| 264 #1 - | |
| -- | Boca Raton, FL : |
| -- | CRC Press, |
| -- | 2020. |
| 264 #4 - | |
| -- | ©2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource : |
| Other physical details | illustrations (black and white) |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 336 ## - | |
| -- | still image |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Chapter 1. Functions Tutorial. Chapter 2. Logic and R. Chapter 3. Sets with R: Building the Tools. Chapter 4. Probability. Chapter 5. Naïve Rule. Chapter 6. Complete Bayes. Chapter 7. Naïve Bayes Classifier. Chapter 8. Stored Model for Naive Bayes Classifier. Chapter 9. Review of Mathematics for Neural Networks. Chapter 10. Calculus. Chapter 11. Neural Networks -- Feed Forward Process and Back Propagation Process. Chapter 12. Programming a Neural Network using OOP in R. Chapter 13. Adding in a Bias Term. Chapter 14. Modular Version of Neural Networks for Deep Learning. Chapter 15. Deep Learning with Convolutional Neural Networks. Chapter 16. R Packages for Neural Networks, Deep Learning, and Naïve Bayes. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R: From the Ground Up reveals how machine learning algorithms do their magic and explains how these algorithms can be implemented in code. It is designed to provide readers with an understanding of the reasoning behind machine learning algorithms as well as how to program them. Written for novice programmers, the book progresses step-by-step, providing the coding skills needed to implement machine learning algorithms in R. The book begins with simple implementations and fundamental concepts of logic, sets, and probability before moving to the coverage of powerful deep learning algorithms. The first eight chapters deal with probability-based machine learning algorithms, and the last eight chapters deal with machine learning based on artificial neural networks. The first half of the book does not require mathematical sophistication, although familiarity with probability and statistics would be helpful. The second half assumes the reader is familiar with at least one semester of calculus. The text guides novice R programmers through algorithms and their application and along the way; the reader gains programming confidence in tackling advanced R programming challenges. Highlights of the book include: More than 400 exercises A strong emphasis on improving programming skills and guiding beginners to the implementation of full-fledged algorithms Coverage of fundamental computer and mathematical concepts including logic, sets, and probability In-depth explanations of machine learning algorithms |
| 588 ## - | |
| -- | OCLC-licensed vendor bibliographic record. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | R (Computer program language) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Programming (Mathematics) |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Artificial Intelligence |
| Source of heading or term | bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Programming / Algorithms |
| Source of heading or term | bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Programming / Object Oriented |
| Source of heading or term | bisacsh |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Taylor & Francis |
| Uniform Resource Identifier | https://www.taylorfrancis.com/books/9781003051220 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | OCLC metadata license agreement |
| Uniform Resource Identifier | http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
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