Data science from scratch : (Record no. 21793)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01925nam a2200241Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250520103029.0 |
| 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 | 9781492041139 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA 76.73.P98 .G78 2019 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Grus, Joel |
| Relator term | author |
| 245 #0 - TITLE STATEMENT | |
| Title | Data science from scratch : |
| Remainder of title | first principles with python / |
| Statement of responsibility, etc. | Joel Grus |
| 250 ## - EDITION STATEMENT | |
| Edition statement | Second Edition. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Sebastopol, California : |
| Name of publisher, distributor, etc. | O'Reilly Media, Incorporated, |
| Date of publication, distribution, etc. | c2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvii, 384 pages : |
| Other physical details | illustrations ; |
| Dimensions | 24 cm. |
| 365 ## - TRADE PRICE | |
| Price amount | USD53 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes index. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Introduction -- A crash course in Python -- Visualizing data -- Linear algebra -- Statistics -- Probability -- Hypothesis and inference -- Gradient descent -- Getting data -- Working with data -- Machine learning -- k-Nearest neighbors -- Naive bayes -- Simple linear regression -- Multiple regression -- Logistic regression -- Decision trees -- Neural networks -- Deep learning -- Clustering -- Natural language processing -- Network analysis -- Recommender systems -- Databases and SQL -- MapReduce -- Data ethics -- Go forth and do data science. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | DATA MINING |
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Library of Congress Classification | Machine Learning | LRC - Main | National University - Manila | General Circulation | 05/07/2024 | Purchased - Amazon | 53.00 | GC QA 76.73.P98 .G78 2019 | NULIB000019552 | 05/20/2025 | c.1 | 05/20/2025 | Books |