Data analysis with open source tools / Philipp K. Janert
Tipo de material:
TextoDetalles de publicación: United States of America : O'Reilly, ©2011Edición: 1a ediciónDescripción: xviii, 509 páginas : ilustraciones ; 24 x 18 centímetrosTipo de contenido: - texto
- sin medio
- volumen
- 9780596802356
- QA76 .9 .D343 J33 2011
| Tipo de ítem | Biblioteca actual | Biblioteca de origen | Colección | Signatura topográfica | Copia número | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | |
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Libros para consulta en sala
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Biblioteca Antonio Enriquez Savignac | Biblioteca Antonio Enriquez Savignac | COLECCIÓN RESERVA | QA76 .9 .D343 J33 2011 (Navegar estantería(Abre debajo)) | 1 | No para préstamo | 036643 |
Navegando Biblioteca Antonio Enriquez Savignac estanterías, Colección: COLECCIÓN RESERVA Cerrar el navegador de estanterías (Oculta el navegador de estanterías)
| QA 76 .9 .D343 A11 2016 Process mining : data science in action / | QA 76 .9 .D343 A26 2015 Data mining : the textbook / | QA 76 .9 .D343 F83 2012 Taming the big data tidal wave : finding opportunities in huge data streams with advanced analytics / | QA76 .9 .D343 J33 2011 Data analysis with open source tools / | QA 76 .9 .D343 J36 2021 Introduction to data mining and analytics with machine learning in R and Python / | QA76 .9 .D343 L185 2019 Hands-On Big Data Analytics with PySpark: Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs / | QA76 .9 .D343 L54 2015 Spatial data mining : theory and application / |
En la cubierta: "A hands-on guide for programmers and data scientists"
1 Introduction - Part I. Graphics: Looking at Data -- 2 A Single Variable: Shape and Distribution -- 3 Two Variables: Establishing Relationships -- 4 Time As a Variable: Time-Series Analysis -- 5 More Than Two Variables: Graphical Multivariate Analysis -- 6 Intermezzo: A Data Analysis Session - Part II -- 7 Guesstimation and the Back of the Envelope -- 8 Models from Scaling Arguments -- 9 Arguments from Probability Models -- 10 What You Really Need to Know About Classical Statistics -- 11 Intermezzo: Mythbusting-Bigfoot, Least Squares, and All That - Part III. Computation: Mining Data -- 12 Simulations -- 13 Finding Clusters -- 14 Seeing the Forest for the Trees: Finding Important Attributes -- 15 Intermezzo: When More Is Different - Part IV. Applications: Using Data -- 16 Reporting, Business Intelligence, and Dashboards -- 17 Financial Calculations and Modeling -- 18 Predictive Analytics -- 19 Epilogue: Facts Are Not Reality
" Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications." -- P. [4]
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