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03541aam a2200421Ii 4500 001 A8475FE2DF0A11E79060ED2797128E48 003 SILO 005 20171212010136 008 170308t20172017njuad 001 0 eng d 010 $a 2017932294 020 $a 1119327636 020 $a 9781119327639 035 $a (OCoLC)974828975 040 $a JRF $b eng $e rda $c JRF $d GK5 $d KLP $d BTCTA $d OCO $d VP@ $d UOK $d BKL $d IBI $d JQM $d YDX $d TOH $d BDX $d IGA $d FSP $d CZA $d NPC $d SFR $d OCLCQ $d IOU $d SILO 050 14 $a T58.5 $b .P54 2017 050 4 $a T58.5 $b .P488 2017 082 04 $a 004 $2 23 082 14 $a 001 $b PIE 2017 100 1 $a Pierson, Lillian, $e author. 245 10 $a Data science for dummies / $c by Lillian Pierson ; foreword by Jake Porway. 246 3 $a Data science 250 $a 2nd edition. 264 1 $a Hoboken, NJ : $b John Wiley and Sons, Inc., $c [2017] 300 $a xvi, 364 pages : $b illustrations, charts ; $c 24 cm. 490 1 $a --For dummies 500 $a Includes index. 520 $a Begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up or "munging" it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations. 505 0 $a Getting Started With Data Science -- Wrapping Your Head around Data Science -- Exploring Data Engineering Pipelines and Infrastructure -- Applying Data-Driven Insights to Business and Industry -- Using Data Science to Extract Meaning from Your Data -- Machine Learning: Learning from Data with your Machine -- Math, Probability, and Statistical Modeling -- Using Clustering to Subdivide Data -- Modeling with Instances -- Building models that Operate Internet-of-Things Devices -- Creating Data Visualizations that Clearly Communicate Meaning -- Following the Principles of Data Visualization Design -- Using D3.js for Data Visualization -- Web-Based Applications for Visualization Design -- Exploring Best Practices in Dashboard Design -- Making Maps from Spatial Data -- Computing for Data Science -- Using Python for Data Science -- Using Open Source R for Data Science -- Using SQL in Data Science -- Doing Data Science with Excel and Knime -- Applying Domain Expertise to Solve Real-World Problems Using Data Science -- Data Science in Journalism: Nailing Down the Five Ws (and an H) -- Delving into Environmental Data Science -- Data Science for Driving Growth in E-Commerce -- Using Data Science to Describe and Predict Criminal Activity -- The Part of Tens --Ten Phenomenal Resources for Open Data -- Ten Free Data Science Tools and Applications. 650 0 $a Information retrieval. 650 0 $a Data mining. 650 0 $a Information technology. 650 0 $a Databases. 700 1 $a Porway, Jake, $e writer of introductory text. 830 0 $a --For dummies. 941 $a 1 952 $l BAPH771 $d 20181228010351.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=A8475FE2DF0A11E79060ED2797128E48 994 $a C0 $b IOUInitiate Another SILO Locator Search