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Tour of data science : learn R and Python in parallel

By: Zhang, Nailong.
Series: Chapman & Hall/CRC big data series.Publisher: Boca Raton : CRC Press, 2021Description: x, 206 p. ; ill., 26 cm.ISBN: 9780367895860.Subject(s): Data mining | R Program Language | Computer program language | Statistics | Optimization | Predictive modelling | Pandas | Linear regression | Logistic regression | Grandient boosting trees | BML traffic model | Gaussian mixture model | Traveling salesman problemDDC classification: 006.312 Summary: A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.
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Item type Current location Call number Status Date due Barcode
Books 006.312 ZHA (Browse shelf) Checked out 13/02/2024 032817

Includes bibliographical references and index.

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.

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