000			02059 a2200253 4500
003			fcuc
005			20250417150519.0
008			250417b |||||||| |||| 00| 0 eng d
020			_a9781009318259
040			_cfcuc
082			_a005.7 TRI 2024
100			_9673 _aTriguero, Isaac _eauthor.
245			_aLarge-scale data analytics with phyton and spark : _ba hands-on guide to implementing machine learning solutions : _cIsaac Triguero and Mikel Galar.
260			_aCambridge, United Kingdom ; New York, NY : _bCambridge University Press, _c2024.
300			_axvi, 378 pages : _billustrations ; _c25 cm.
504			_aIncludes bibliographical references and index.
520			_a"Based on the authors' extensive teaching experience, this hands-on graduate-level textbook teaches how to carry out large-scale data analytics and design machine learning solutions for big data. With a focus on fundamentals, this extensively class-tested textbook walks students through key principles and paradigms for working with large-scale data, frameworks for large-scale data analytics (Hadoop, Spark), and explains how to implement machine learning to exploit big data. It is unique in covering the principles that aspiring data scientists need to know, without detail that can overwhelm. Real-world examples, hands-on coding exercises and labs combine with exceptionally clear explanations to maximize student engagement. Well-defined learning objectives, exercises with online solutions for instructors, lecture slides, and an accompanying suite of lab exercises of increasing difficulty in Jupyter Notebooks offer a coherent and convenient teaching package. An ideal teaching resource for courses on large-scale data analytics with machine learning in computer/data science departments."-- Provided by publisher.
650			_aSpark _x(Electronic resource : Apache Software Foundation)
650			_aBig data
650			_aMachine learning
650			_aPython _x(Computer program language)
700			_aGalar, Mikel _eauthor.
942			_2ddc _c3
999			_c60373 _d60373