Machine learning for absolute beginners : (Record no. 21730)
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fixed length control field | 01844nam a2200241Ia 4500 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | NULRC |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20250520103028.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 250520s9999 xx 000 0 und d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9798558098426 |
040 ## - CATALOGING SOURCE | |
Transcribing agency | NULRC |
050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q 325.5 .T44 2021 |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Theobald, Oliver |
Relator term | author |
245 #0 - TITLE STATEMENT | |
Title | Machine learning for absolute beginners : |
Remainder of title | a plain English introduction / |
Statement of responsibility, etc. | Oliver Theobald |
250 ## - EDITION STATEMENT | |
Edition statement | Third Edition. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
Place of publication, distribution, etc. | [United States] : |
Name of publisher, distributor, etc. | Scatterplot Press, |
Date of publication, distribution, etc. | c2021 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 179 pages : |
Other physical details | illustrations ; |
Dimensions | 23 cm. |
365 ## - TRADE PRICE | |
Price amount | USD16 |
505 ## - FORMATTED CONTENTS NOTE | |
Formatted contents note | Preface -- What is Machine Learning ? -- Machine Learning Categories -- The Machine Learning Toolbox -- Data Scrubbing Setting up your data -- Linear Regression -- Logistic Regression -- k-Nearest -- k-Means Clustering -- Bias & Variance -- Support Vector Machines -- Artificial Neural Networks -- Decision Trees -- Ensemble Modeling -- Development Environment -- Building a Model in Python -- Model Optimization -- Next Steps -- Thank You -- Bug Bounty -- Further Resources -- Appendix: Introduction to Python. |
520 ## - SUMMARY, ETC. | |
Summary, etc. | Machine Learning for Absolute Beginners has been written and designed for absolute beginners. This means plain English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing specific algorithms applied in machine learning, including their pros and cons. At the end of the book, I share insights and advice on further learning and careers in this space |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | MACHINE LEARNING |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Pedersen, Jeremy |
Relator term | editor |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | Library of Congress Classification |
Koha item type | Books |
Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
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Library of Congress Classification | Digital Forensic | LRC - Main | National University - Manila | General Circulation | 03/11/2024 | Purchased - Amazon | 16.00 | GC Q 325.5 .T44 2021 | NULIB000019489 | 05/20/2025 | c.1 | 05/20/2025 | Books |