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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media (edition 2), 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
Paperback. Condition: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media (edition 2), 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
Paperback. Condition: Good. 2. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Seller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 5 out of 5 stars
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Condition: good. This book is in good condition. The cover has minor creases or bends. The binding is tight and pages are intact. Some pages may have writing or highlighting.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media June 2020, 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
Trade Paperback. Condition: VG. used trade paperback edition. lightly shelfworn, corners perhaps slightly bumped. pages and binding are clean, straight and tight. there are no marks to the text or other serious flaws.
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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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paperback. Condition: Good. 2nd Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Condition: New. Idioma/Language: Español. Los métodos estadísticos son una parte fundamental de la ciencia de datos, pero pocos científicos de datos tienen una formación avanzada en estadística. Los cursos y libros sobre estadística básica rara vez tratan el tema desde la perspectiva de la ciencia de datos. La segunda edición de este libro incluye ejemplos detallados de Python, ofrece una orientación práctica sobre la aplicación de los métodos estadísticos a la ciencia de datos, te indica cómo evitar su uso incorrecto y te aconseja sobre lo que es y lo que no es importante. Muchos recursos de la ciencia de datos incorporan métodos estadísticos, pero carecen de una perspectiva estadística más profunda. Si estás familiarizado con los lenguajes de programación R o Python y tienes algún conocimiento de estadística, este libro suple esas carencias de una forma práctica, accesible y clara. Con este libro aprenderás:Por qué el análisis exploratorio de datos es un paso preliminar clave en la ciencia de datosCómo el muestreo aleatorio puede reducir el sesgo y ofrecer un conjunto de datos de mayor calidad, incluso con Big DataCómo los principios del diseño experimental ofrecen respuestas definitivas a preguntasCómo utilizar la regresión para estimar resultados y detectar anomalíasTécnicas de clasificación esenciales para predecir a qué categorías pertenece un registroMétodos estadísticos de aprendizaje automático que «aprenden» a partir de los datosMétodos de aprendizaje no supervisados para extraer significado de datos sin etiquetarPeter Bruce es el fundador del Institute for Statistics Education en Statistics. com. Andrew Bruce es científico investigador jefe en Amazon y tiene más de 30 años de experiencia en estadística y ciencia de datos. Peter Gedeck es científico de datos senior en Collaborative Drug Discovery, desarrolla algoritmos de aprendizaje automático para pronosticar propiedades de posibles futuros fármacos. 10 *** Nota: Los envíos a España peninsular, Baleares y Canarias se realizan a través de mensajería urgente. No aceptamos pedidos con destino a Ceuta y Melilla.
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Paperback. Condition: New. 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 scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media
paperback. Condition: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
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ESTADISTICA PRACTICA PARA CIENCIA DE DATOS CON R Y PYTHON
Published by MARCOMBO EDICIONES TECNICAS, 2022
ISBN 10: 842673443X ISBN 13: 9788426734433
Language: Spanish
Condition: Nuevo. O'REILLY - ENSAYOS LITERARIOS# INFORMATICA: CUESTIONES GENERALES# PROGRAMACION DE GRAFICOS.
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ESTADISTICA PRACTICA PARA CIENCIA DE DATOS CON R Y PYTHON
Published by MARCOMBO EDICIONES TECNICAS, España, 2022
ISBN 10: 842673443X ISBN 13: 9788426734433
Language: Spanish
Rústica. Condition: Nuevo. Dust Jacket Condition: Nuevo. AZTUNIV.
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketCondition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
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Practical Statistics for Data Scientists
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
£ 65.60
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Add to basketPaperback. Condition: New. 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 scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data.
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Condition: New.
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Condition: New.
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Rustica (tapa blanda). Condition: New. Dust Jacket Condition: Nuevo. 01. Los métodos estadísticos son una parte fundamental de la ciencia dedatos, pero pocos científicos de datos tienen una formación avanzadaen estadística. Los cursos y libros sobre estadística básica rara veztratan el tema desde la perspectiva de la ciencia de datos. La segunda edición de este libro incluye ejemplos detallados de Python, ofreceuna orientación práctica sobre la aplicación de los métodosestadísticos a la ciencia de datos, te indica cómo evitar su usoincorrecto y te aconseja sobre lo que es y lo que no es importante.Muchos recursos de la ciencia de datos incorporan métodosestadísticos, pero carecen de una perspectiva estadística másprofunda. Si estás familiarizado con los lenguajes de programación R o Python y tienes algún conocimiento de estadística, este libro supleesas carencias de una forma práctica, accesible y clara. Con estelibro aprenderás: Por qué el análisis exploratorio de datos es un paso preliminar clave en la ciencia de datos Cómo el muestreo aleatoriopuede reducir el sesgo y ofrecer un conjunto de datos de mayorcalidad, incluso con Big Data Cómo los principios del diseñoexperimental. LIBRO.
