The Locator -- [(subject = "Data mining")]

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02207aam a2200397 i 4500
001 9F6CA5E6F0B811EE9EC0998A3BECA4DB
003 SILO
005 20240402011628
008 230502t20232023enka     b    001 0 eng d
010    $a 2023942926
020    $a 1398612324
020    $a 9781398612327
020    $a 1398612340
020    $a 9781398612341
035    $a (OCoLC)1389776915
040    $a UKMGB $b eng $e rda $c UKMGB $d OCLCO $d UOK $d YDX $d OCO $d OCLCF $d SILO
050  4 $a QA76.9.D343 $b N45 2023
082 04 $a 006.3/12 $2 23/eng/20230920
100 1  $a Nelson, Adam Ross, $e author.
245 10 $a Confident data science : $b discover the essential skills of data science / $c Adam Ross Nelson.
264  1 $a London, United Kingdom ; $b KoganPage, $c 2023.
300    $a xv, 386 pages : $b illustrations ; $c 22 cm.
490 0  $a Confident series
504    $a Includes bibliographical references and index.
520    $a "With Confident Data Science, learn the essential skills and build your confidence in this sector through key insights and practical tools for success. In this book, you will discover all of the skills you need to understand this discipline, from primers on the key analytic and visualization tools to tips for pitching to and working with clients. Adam Ross Nelson draws upon his expertise as a data science consultant and, as someone who made moved into the industry late in his career, to provide an overview of data science, including its key concepts, its history and the knowledge required to become a successful data scientist. Whether you are considering a career in this industry or simply looking to expand your knowledge, Confident Data Science is the essential guide to the world of data science."-- $c Amazon.com.
650  0 $a Data mining.
650  0 $a Computer science.
650  6 $a Exploration de données (Informatique)
650  6 $a Informatique.
650  7 $a Computer science. $2 fast $0 (OCoLC)fst00872451
650  7 $a Data mining. $2 fast $0 (OCoLC)fst00887946
776 08 $i ebook version : $z 9781398612334
941    $a 1
952    $l UNUX074 $d 20240402013527.0
956    $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=9F6CA5E6F0B811EE9EC0998A3BECA4DB
994    $a Z0 $b NIU
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