Doing data science /
Schutt, Rachel
Doing data science / Rachel Schutt and Cathy O'Neil. - [Place of publication not identifed] : [publisher not identified], c2014 - xxiv, 375 pages : illustrations ; 23 cm.
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.
A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering
9781449358655
BIG DATA
QA 76.9 .S37 2014
Doing data science / Rachel Schutt and Cathy O'Neil. - [Place of publication not identifed] : [publisher not identified], c2014 - xxiv, 375 pages : illustrations ; 23 cm.
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.
A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering
9781449358655
BIG DATA
QA 76.9 .S37 2014