TY  - BOOK
AU  - Schutt, Rachel
AU  - Schutt, Rachel
TI  - Doing data science
SN  - 9781449358655
AV  - QA 76.9 .S37 2014 
PY  - 2014///
CY  - [Place of publication not identifed]
PB  - [publisher not identified]
KW  - BIG DATA
N1  - Includes index; 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
N2  - A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering
ER  -