04705cam a2200589Ii 4500 9781003020646 FlBoTFG 20260210180741.0 m o d cr cnu|||unuuu 201130s2021 enk ob 001 0 eng d OCoLC-P eng rda pn OCoLC-P 9781003020646 (electronic bk.) 100302064X (electronic bk.) 9781000215274 (electronic bk. : EPUB) 100021527X (electronic bk. : EPUB) 9780367895860 9781000215236 (electronic bk. : Mobipocket) 1000215237 (electronic bk. : Mobipocket) 9780367897062 9781000215199 (electronic bk. : PDF) 1000215199 (electronic bk. : PDF) (OCoLC)1224544725 (OCoLC-P)1224544725 QA76.9.D343 Z458 2021eb COM 051360 bisacsh COM 051010 bisacsh COM 012040 bisacsh UN bicssc 006.3/12 23 Zhang, Nailong, author. A tour of data science : learn R and Python in parallel / Nailong Zhang. First edition. Abingdon, Oxon ; Boca Raton, FL : CRC Press, 2021. 1 online resource (x, 206 pages). text txt rdacontent computer c rdamedia online resource cr rdacarrier Chapman & Hall/CRC big data series 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. Assumptions about the readers backgroundBook overviewIntroduction to R/Python ProgrammingCalculatorVariable and TypeFunctionsControl flowsSome built-in data structuresRevisit of variablesObject-oriented programming (OOP) in R/PythonMiscellaneousMore on R/Python ProgrammingWork with R/Python scriptsDebugging in R/PythonBenchmarkingVectorizationEmbarrassingly parallelism in R/PythonEvaluation strategySpeed up with C/C++ in R/PythonA first impression of functional programming Miscellaneousdata.table and pandasSQLGet started with data.table and pandasIndexing & selecting dataAdd/Remove/UpdateGroup byJoinRandom Variables, Distributions & Linear RegressionA refresher on distributionsInversion sampling & rejection samplingJoint distribution & copulaFit a distributionConfidence intervalHypothesis testingBasics of linear regressionRidge regressionOptimization in PracticeConvexityGradient descentRoot-findingGeneral purpose minimization tools in R/PythonLinear programmingMiscellaneousMachine Learning - A gentle introductionSupervised learningGradient boosting machineUnsupervised learningReinforcement learningDeep Q-NetworksComputational differentiationMiscellaneous "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"-- Provided by publisher. OCLC-licensed vendor bibliographic record. COMPUTERS / Programming Languages / Python bisacsh COMPUTERS / Programming Languages / General bisacsh COMPUTERS / Computer Graphics / Game Programming & Design bisacsh Data mining. 3098 R (Computer program language) Python (Computer program language) Taylor & Francis https://www.taylorfrancis.com/books/9781003020646 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 90175 90174