MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01584nam a22002777i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250722160934.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
250722s2021 ii ao||fr|||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789389423617 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
EG-GaU |
| Transcribing agency |
EG-GaU |
| Modifying agency |
EG-GaU |
| Description conventions |
rda |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
23 |
| Classification number |
006.3 |
| Item number |
c.e.b. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Chopra, Deepti, |
| Relator term |
author. |
| 9 (RLIN) |
60466 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Building machine learning systems using Python : |
| Remainder of title |
practice to train predictive models and analyze machine learning results with real use‑cases / |
| Statement of responsibility, etc. |
Dr Deepti Chopra. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
New Delhi : |
| Name of producer, publisher, distributor, manufacturer |
BPB Publications, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2021. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
136 pages ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references.<br/> |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1. Introduction to Machine Learning ‡ 2. Linear Regression ‡ 3. Classification Using Logistic Regression ‡ 4. Overfitting and Regularization ‡ 5. Feasibility of Learning ‡ 6. Support Vector Machine ‡ 7. Neural Network ‡ 8. Decision Trees ‡ 9. Unsupervised Learning ‡ 10. Theory of Generalization ‡ 11. Bias and Fairness in ML.<br/> |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
A beginner‑friendly guide to machine learning with practical implementations of regression, classification, clustering, SVM, decision trees, neural networks, and unsupervised learning using Python and scikit‑learn. :contentReference[oaicite:1]{index=1}<br/> |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Predictive analytics. |
| 9 (RLIN) |
60467 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |