Articles - R Conference

Introduction to parallel computing with R

kassambara | 03/08/2017 | 322 | Post a comment | R Conference | useR 2017, Big data, Parallel computing

Introduction to parallel computing with R

Source: useR 2017

0 Note

Enjoyed this article? Give us 5 stars (just above this text block)! Reader needs to be STHDA member for voting. I’d be very grateful if you’d help it spread by emailing it to a friend, or sharing it on Twitter, Facebook or Linked In.

Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!

Avez vous aimé cet article? Donnez nous 5 étoiles (juste au dessus de ce block)! Vous devez être membre pour voter. Je vous serais très reconnaissant si vous aidiez à sa diffusion en l'envoyant par courriel à un ami ou en le partageant sur Twitter, Facebook ou Linked In.

Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!

Recommended for You!

Machine Learning Essentials: Practical Guide in R

Practical Guide to Cluster Analysis in R

Practical Guide to Principal Component Methods in R

R Graphics Essentials for Great Data Visualization

Network Analysis and Visualization in R

More books on R and data science

Recommended for you

This section contains best data science and self-development resources to help you on your path.

Coursera - Online Courses and Specialization

Data science

Course: Machine Learning: Master the Fundamentals by Standford
Specialization: Data Science by Johns Hopkins University
Specialization: Python for Everybody by University of Michigan
Courses: Build Skills for a Top Job in any Industry by Coursera
Specialization: Master Machine Learning Fundamentals by University of Washington
Specialization: Statistics with R by Duke University
Specialization: Software Development in R by Johns Hopkins University
Specialization: Genomic Data Science by Johns Hopkins University

Popular Courses Launched in 2020

Google IT Automation with Python by Google
AI for Medicine by deeplearning.ai
Epidemiology in Public Health Practice by Johns Hopkins University
AWS Fundamentals by Amazon Web Services

Trending Courses

The Science of Well-Being by Yale University
Google IT Support Professional by Google
Python for Everybody by University of Michigan
IBM Data Science Professional Certificate by IBM
Business Foundations by University of Pennsylvania
Introduction to Psychology by Yale University
Excel Skills for Business by Macquarie University
Psychological First Aid by Johns Hopkins University
Graphic Design by Cal Arts

Books - Data Science

Our Books

Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
Network Analysis and Visualization in R by A. Kassambara (Datanovia)
Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)

Others

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
Deep Learning with R by François Chollet & J.J. Allaire
Deep Learning with Python by François Chollet

Comments

You are not authorized to post a comment