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:
Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Nailong Zhang is lead Data Scientist at Mass Mutual Life Insurance Company.
This book covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single and short book. It does not cover everything, but instead, teaches the key concepts and topics. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 parallelCover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools data.table and pandasProvides a concise and accessible presentationIncludes 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. 218 pp. Englisch. Codice articolo 9780367897062
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