Cargando…

Improve your data quality using sampling distribution: practical statistics for data science

Detalles Bibliográficos
Autores principales:	Bruce, Peter C, Bruce, Andrew
Lenguaje:	eng
Publicado:	O'Reilly 2016
Materias:	Computing and Computers
Acceso en línea:	http://cds.cern.ch/record/2254251

Ejemplares similares

Improve the outcome of your data experiments with A-B testing: practical statistics for data science
por: Bruce, Peter C, et al.
Publicado: (2016)

Practical statistics for data scientists: 50 essential concepts
por: Bruce, Peter, et al.
Publicado: (2017)

Data and Goliath: the hidden battles to capture your data and control your world
por: Schneier, Bruce
Publicado: (2015)

Simulation for data science with R: harness actionable insights from your data with computational statistics and simulations using R
por: Templ, Matthias
Publicado: (2016)

Julia for data science: explore the world of data science from scratch with Julia by your side
por: Joshi, Anshul
Publicado: (2016)

New advances in statistics and data science
por: Chen, Ding-Geng, et al.
Publicado: (2018)

Data science in practice
por: Said, Alan, et al.
Publicado: (2018)

Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data
por: Ratner, Bruce
Publicado: (2011)

Data science for marketing analytics: achieve your marketing goals with the data analytics power of Python
por: Blanchard, Tommy, et al.
Publicado: (2019)

Data science: concepts and practice
por: Kotu, Vijay, et al.
Publicado: (2018)

Practical data science cookbook
por: Tattar, Prabhanjan, et al.
Publicado: (2017)

Data analysis and statistics for geography, enviromental science, and engineering
por: Acevedo, Miguel F
Publicado: (2013)

Clojure for data science: statistics, big data, and machine learning for Clojure programmers
por: Garner, Henry
Publicado: (2015)

Statistics for data science: leverage the power of statistics for data analysis, classification, regression, machine learning, and neural networks
por: Miller, James D
Publicado: (2017)

Principles of data science: learn the techniques and math you need to start making sense of your data
por: Ozdemir, Sinan
Publicado: (2016)

Julia 1.0 programming cookbook: over 100 numerical and distributed computing recipes for your daily data science workflow
por: Kamiński, Bogumił, et al.
Publicado: (2018)

Training systems using Python statistical modeling: explore popular techniques for modeling your data in Python
por: Miller, Curtis
Publicado: (2019)

Educating data: using data science to improve learning, motivation, and persistence
por: Martin, Taylor
Publicado: (2015)

Applied data science with Python and Jupyter: use powerful industry-standard tools to unlock new, actionable insights from your data
por: Galea, Alex
Publicado: (2018)

Practical business intelligence: learn to get the most our of your business data to optimize your business
por: Sherif, Ahmed
Publicado: (2016)

Managing your data science projects: learn salesmanship, presentation, and maintenance of completed models
por: De Graaf, Robert W
Publicado: (2019)

Jupyter for data science: exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter
por: Toomey, Dan
Publicado: (2017)

Practical data science cookbook: practical recipes on data pre-processing, analysis and visualization using R and Python
por: Tattar, Prabhanjan, et al.
Publicado: (2017)

Metaprogramming in R: advanced statistical programming for data science, analysis and finance
por: Mailund, Thomas
Publicado: (2017)

Optimize your greatest asset: your people : how to apply analytics to big data to improve your human capital investments
por: Pease, Gene
Publicado: (2015)

Practical data wrangling: expert techniques for transforming your raw data into a valuable source for analytics
por: Visochek, Allan
Publicado: (2017)

Practical data science with SAP: machine learning techniques for enterprise data
por: Foss, Greg, et al.
Publicado: (2019)

Machine learning for data mining: improve your data mining capabilities with advanced predictive modeling
por: Salcedo, Jesus
Publicado: (2019)

Improving the user experience through practical data analytics: gain meaningful insight and increase your bottom line
por: Fritz, Mike, et al.
Publicado: (2015)

Spark for data science: analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0
por: Duvvuri, Srinivas
Publicado: (2016)

Mastering data analysis with R: gain clear insights into your data and solve real-world data science problems with R--from data munging to modeling and visualization
por: Daróczi, Gergely
Publicado: (2015)

Python data structures and algorithms: improve the performance and speed of your applications
por: Baka, Benjamin
Publicado: (2017)

Numbersense: how to use big data to your advantage
por: Fung, Kaiser
Publicado: (2013)

Functional programming in R: advanced statistical programming for data science, analysis and finance
por: Mailund, Thomas
Publicado: (2017)

Implement, improve and expand your statewide longitudinal data system: creating a culture of data in education
por: McQuiggan, Jamie, et al.
Publicado: (2014)

Practical data science with Python 3: synthesizing actionable insights from data
por: Varga, Ervin
Publicado: (2019)

Principles of data science: a beginner's guide to statistical techniques and theory to build effective data-driven applications
por: Ozdemir, Sinan, et al.
Publicado: (2018)

Data science with Java: practical methods for scientists and engineers
por: Brzustowicz, Michael R
Publicado: (2017)

Mathematical problems in data science: theoretical and practical methods
por: Chen, Li M, et al.
Publicado: (2015)

Data fluency : empowering your organization with effective data communication
por: Gemignani, Zach, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_g4u3nirel1f9cv86849fceiebl