Library of American University of Madaba
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O'Neil, Cathy,
Doing data science / Subtitle on cover: Straight talk from the frontline Cathy O'Neil and Rachel Schutt. - Sebastopol, CA : O'Reilly, 2014. - xxv, 377 p. : ill. (col.) ; 23 cm.
2013-10-08: first release ; 2013-12-13: second release ; 2014-10-10: third release. 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 engines : building a user-facing data product at scale -- Data visualization and fraud detection -- Social networks and data journalism -- Causality -- Epidemiology -- Lessons learned from data competitions : data leakage and model evaluation -- Data engineering : MapReduce, Pregel, and Hadoop -- 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 (pbk.) 1449358659 (pbk.)
Data mining.
Big data.
Information science.
Data structures (Computer science)
Database management.
Cyberinfrastructure.
006.31 / O586
Doing data science / Subtitle on cover: Straight talk from the frontline Cathy O'Neil and Rachel Schutt. - Sebastopol, CA : O'Reilly, 2014. - xxv, 377 p. : ill. (col.) ; 23 cm.
2013-10-08: first release ; 2013-12-13: second release ; 2014-10-10: third release. 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 engines : building a user-facing data product at scale -- Data visualization and fraud detection -- Social networks and data journalism -- Causality -- Epidemiology -- Lessons learned from data competitions : data leakage and model evaluation -- Data engineering : MapReduce, Pregel, and Hadoop -- 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 (pbk.) 1449358659 (pbk.)
Data mining.
Big data.
Information science.
Data structures (Computer science)
Database management.
Cyberinfrastructure.
006.31 / O586