Schutt, Rachel <br/><br/>
Doing data science / 
Rachel Schutt and Cathy O'Neil. 
 - [Place of publication not identifed] :  [publisher not identified],  c2014 
 - xxiv, 375 pages :  illustrations ;  23 cm. 
<br/><br/>Includes index. 
<br/><br/>Introduction : what is data science? -- Statistical inference, exploratory data analysis, and the data science process -- Algorithms -- Spam filters, Naive  Bayes, and wrangling -- Logistic regression -- Time stamps and financial modeling -- Extracting meaning from data -- Recommendation engine : building a user-facing data product -- Data visualization and fraud detection -- Social networks and data journalism -- Causality -- Epidemiology -- Lessons learned from data competitions -- Data engineering -- The Students speak -- Next-generation data scientists, Hubris and ethics. 
<br/><br/> A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering 
<br/><br/><label>ISBN: </label>9781449358655 
<br/><br/><label>Subjects--Topical Terms: </label><br/>BIG DATA
<br/><br/><label>LC Class. No.: </label>QA 76.9 .S37 2014