| 000 -LEADER |
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| fixed length control field |
nam a22 7a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
190613b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783319554433 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Item number |
SKI |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Skiena, Steven S. |
| 245 ## - TITLE STATEMENT |
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| Title |
Data science design manual |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2017 |
| Place of publication, distribution, etc |
New York : |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xvii, 445 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 365 ## - TRADE PRICE |
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| Price amount |
52.99 |
| Price type code |
EUR |
| Unit of pricing |
00 |
| 490 ## - SERIES STATEMENT |
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| Series statement |
Texts in computer science. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop”. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Visualization |
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| Topical term or geographic name as entry element |
Knowledge Discovery |
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| Topical term or geographic name as entry element |
Data Mining |
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| Topical term or geographic name as entry element |
Quantitative research |
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| Topical term or geographic name as entry element |
Big data |
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| Topical term or geographic name as entry element |
Computer Science |
|
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| Topical term or geographic name as entry element |
Data processing |
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| Topical term or geographic name as entry element |
Mathematical statistics |
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| Topical term or geographic name as entry element |
Statistics Programs |
|
|---|
| Topical term or geographic name as entry element |
Quantitative research |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
|
| Item type |
Books |