robert pries (34 resultados)

8°, 32 S., kart., guter Zustand. 42328.

Rustica. Condición: Perfecta Sin Estrenar. En Castellano. El precio de los gastos de envío está calculado para libros con un peso máximo de1 kg superando el kg los gastos de envió serán mayores, - Los pedidos fuera de la península: Baleares ,Canarias, Ceuta y Melilla tienen un coste adicional, consúltenos antes de realizar su pedido, los libros usados pueden tener o no firma del anterior propietario------------ Causas , efectos y cómo superarlos Size: 14x22---160 Pag. Guía.

Halbleinen. Condición: Gut. 20 cm 298 S. Halbleinen (Blauer Leinen). Zustand: Gut gering gebräunt u. wellig (Innen); Großer Schrifteintrag vor dem Titelblatt; Seiten altersbedingt stellenweise leicht braunfleckig; Einband (Außen) hat leichte Gebrauchsspuren; Schnitt ist leicht braunfleckig, oben leicht angestaubt; Seitlicher Vorderdeckel u. oberer Hinterdeckel sind an zwei Stellen leicht bestoßen; Es fehlt ein kleines Stück vom rechts Hinterdeckel; Schutzumschlag fehlt, oder es gibt keinen; * Die Photos sind original von uns erstellt worden, u.a. erkennbar an einem kleinen weißen Stück Papier im oberen Schnitt. Ab und an verwenden Suchmaschinen Verlagsphotos, bei den Portalen selbst, werden aber nur unsere Originalphotos gezeigt.

Ln. mit Goldschrift, stockfleckig, leicht angebräunt, Fraktur, marmorierter Schnitt, guter Zustand.

Encuadernación de tapa blanda. Condición: Aceptable. G64648 Plural. Arco., Barcelona., 1992. Rústica editorial. Fotos en b/n. 160pp. L. AUTOAYUDA.

Condición: New.

Paperback. Condición: New. With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package.The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses.Describes the benefits of distributed computing in simple termsIncludes substantial vendor/tool material, especially for open source decisionsCovers prominent software packages, including Hadoop and Oracle EndecaExamines GIS and machine learning applicationsConsiders privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken.The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.

Condición: New.

Paperback. Condición: New.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New. In.

Paperback. Condición: New. With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package.The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses.Describes the benefits of distributed computing in simple termsIncludes substantial vendor/tool material, especially for open source decisionsCovers prominent software packages, including Hadoop and Oracle EndecaExamines GIS and machine learning applicationsConsiders privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken.The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.

Condición: New. 1st edition NO-PA16APR2015-KAP.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. Kim H. Pries has four college degrees: a bachelor of arts in history from the University of Texas at El Paso (UTEP), a bachelor of science in metallurgical engineering from UTEP, a master of science in engineering from UTEP, and a master.

Paperback. Condición: New. With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package.The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses.Describes the benefits of distributed computing in simple termsIncludes substantial vendor/tool material, especially for open source decisionsCovers prominent software packages, including Hadoop and Oracle EndecaExamines GIS and machine learning applicationsConsiders privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken.The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.

Gr.-8°. 208 Seiten. Kartoniert. Archiv-Aufkleber des Wachholtz Verlages auf dem Vorderdeckel und vorderem Vorsatz. Band ansonsten in sehr gutem, ungelesenem Zustand. Seiten ungeschnitten! (Quellen und Forschungen zur Geschichte Schleswig-Holsteins, Band 32).

Condición: As New. Unread book in perfect condition.

Condición: New.

Paperback. Condición: New. With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package.The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses.Describes the benefits of distributed computing in simple termsIncludes substantial vendor/tool material, especially for open source decisionsCovers prominent software packages, including Hadoop and Oracle EndecaExamines GIS and machine learning applicationsConsiders privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken.The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.

Condición: As New. Unread book in perfect condition.

Halbleinen. 345 Seiten. (Frakturschrift) Signatur von alter Hand sowie Stempel auf dem Vorsatz. Geringe Lagerspuren. Sehr gutes Studienexemplar. Sprache: Deutsch Gewicht in Gramm: 750.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. pp. 536.

Condición: New. pp. 536.

Hardcover. Condición: Brand New. 556 pages. 9.75x6.75x1.25 inches. In Stock.

Condición: New.

Gebunden. Condición: New. Kim H. Pries has four college degrees: a bachelor of arts in history from the University of Texas at El Paso (UTEP), a bachelor of science in metallurgical engineering from UTEP, a master of science in engineering from UTEP, and a master.