Machine learning with R (Record no. 1589)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02049 a2200217 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20190207140422.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 190207b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781784393908 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | IIMV |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Brett Lantz |
| Relator term | Author |
| 9 (RLIN) | 877 |
| 245 1# - TITLE STATEMENT | |
| Title | Machine learning with R |
| Remainder of title | Discover how to build machine learning algorithms, prepare data,and dig deep into data prediction techniques with R |
| Statement of responsibility, etc. | by Brett Lantz |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Name of publisher, distributor, etc. | Packt |
| Date of publication, distribution, etc. | 2015 |
| Place of publication, distribution, etc. | Mumbai |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xiii, 426 pages: |
| Other physical details | Ilustrations; |
| Dimensions | 24 cm. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1 Introducing Machine Learning<br/>2 Managing and Understanding Data<br/>3 Lazy Learning – Classification Using Nearest Neighbors<br/>4 Probabilistic Learning – Classification Using Naive Bayes<br/>5 Divide and Conquer – Classification Using Decision Trees and Rules<br/>6 Forecasting Numeric Data – Regression Methods<br/>7 Black Box Methods – Neural Networks and Support Vector Machines<br/>8 Finding Patterns – Market Basket Analysis Using Association Rules<br/>9 Finding Groups of Data – Clustering with k-means<br/>10 Evaluating Model Performance<br/>11 Improving Model Performance<br/>12 Specialized Machine Lea |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | Updated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience.<br/><br/>With this book, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. Through full engagement with the sort of real-world problems data-wranglers face, you'll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Source of heading or term | Computer Science |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Book |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Total Renewals | Full call number | Barcode | Date last seen | Date last checked out | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Non-fiction | Indian Institute of Management Visakhapatnam | Indian Institute of Management Visakhapatnam | General Stacks | 02/05/2019 | 9 | 899.25 | 10 | 8 | 006.31 LAN | 001058 | 03/05/2024 | 10/30/2023 | 1199.00 | 02/05/2019 | Book |