Practical statistics data scientists de bruce peter (24 resultados)
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Librería: WeBuyBooks, Rossendale, LANCS, Reino UnidoWeBuyBooks
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Librería: CollegePoint, Inc, Jamestown, TN, Estados Unidos de AmericaCollegePoint, Inc
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Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
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Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
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Paperback. Condición: USED BOOKS. USED BOOKS ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges wil…l be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Librería: medimops, Berlin, Alemaniamedimops
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Librería: medimops, Berlin, Alemaniamedimops
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Librería: medimops, Berlin, Alemaniamedimops
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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Paperback. Condición: new. Paperback. Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides… practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that ""learn"" from data Unsupervised learning methods for extracting meaning from unlabeled data" Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on whats important and whats not Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: medimops, Berlin, Alemaniamedimops
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 2nd edition. 342 pages. 9.00x7.00x0.75 inches. In Stock.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 104,67
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Paperback. Condición: new. Paperback. Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides… practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that ""learn"" from data Unsupervised learning methods for extracting meaning from unlabeled data" Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on whats important and whats not Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: liu xing, Nanjing, JS, Chinaliu xing
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EUR 105,18
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paperback. Condición: New. Paperback. Pub Date: 2018-02-01 Publisher: southeast university press. a lot of scientific data resources include statistical methods. but the lack of depth of statistical perspective.If you are familiar with the R language programming. also with statistics. the quick reference will help you set up to…learn to the knowledge of Bridges.You will learn from the book: why exploratory data analysis is the number.
