Mastering Spark with R - The Complete Guide to Large-Scale Analysis and Modeling

A guide to large-scale analysis and modelling when using R through Spark.

Info autore

Javier is a software engineer with experience in technologies ranging from desktop, web, mobile and backend, to augmented reality and deep learning applications. He previously worked for Microsoft Research and SAP and holds a double degree in Mathematics and Software Engineering. He is the author of various R packages like sparklyr, cloudml, r2d3, mlflow, tfdeploy and kerasjs.

Kevin builds open source libraries for machine learning and model deployment. He has held data science positions in various industries including insurance where he was a credentialed actuary. Kevin is the creator of mlflow, mleap, sparkxgb among various R packages. He is also an amateur mixologist and sommelier.

Edgar Ruiz has a background in deploying enterprise reporting and business intelligence solutions. He is the author of multiple articles and blog posts sharing analytics insights and server infrastructure for data science. Edgar is the author and administrator of the db.rstudio.com web site, and the current administrator of the sparklyr web site. He's also the co-author of the dbplyr package, and creator of the dbplot, tidypredict and the modeldb package.

Riassunto

With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems.

Dettagli sul prodotto

• Autori: Kevin Kuo, Javier Luraschi, Edgar Ruiz
• Editore: O'Reilly
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 31.10.2019
• EAN: 9781492046370
• ISBN: 978-1-4920-4637-0
• Dimensioni: 178 mm x 233 mm x 26 mm
• Peso: 512 g
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Linguaggi di programmazione; Data Mining, COMPUTERS / Computer Science, TECHNOLOGY & ENGINEERING / Electronics / General, computer science, Information visualization, information architecture, Electronics engineering, Programming & scripting languages: general, COMPUTERS / Human-Computer Interaction (HCI), COMPUTERS / Computer Architecture, Database design and theory, COMPUTERS / Data Science / Data Visualization, Programming and scripting languages: general, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Database Administration & Management, Data capture and analysis, Data Capture & Analysis, COMPUTERS / Languages / General, Database design & theory