Data mining and machine learning software | Numerical analysis software for Linux | Free statistical software
Programming with Big Data in R (pbdR) is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical software. The significant difference between pbdR and R code is that pbdR mainly focuses on distributed memory systems, where data are distributed across several processors and analyzed in a batch mode, while communications between processors are based on MPI that is easily used in large high-performance computing (HPC) systems. R system mainly focuses on single multi-core machines for data analysis via an interactive mode such as GUI interface. Two main implementations in R using MPI are Rmpi and pbdMPI of pbdR. * The pbdR built on pbdMPI uses SPMD parallelism where every processor is considered as worker and owns parts of data. The SPMD parallelism introduced in mid 1980 is particularly efficient in homogeneous computing environments for large data, for example, performing singular value decomposition on a large matrix, or performing clustering analysis on high-dimensional large data. On the other hand, there is no restriction to use manager/workers parallelism in SPMD parallelism environment. * The Rmpi uses manager/workers parallelism where one main processor (manager) serves as the control of all other processors (workers). The manager/workers parallelism introduced around early 2000 is particularly efficient for large tasks in small clusters, for example, bootstrap method and Monte Carlo simulation in applied statistics since i.i.d. assumption is commonly used in most statistical analysis. In particular, task pull parallelism has better performance for Rmpi in heterogeneous computing environments. The idea of SPMD parallelism is to let every processor do the same amount of work, but on different parts of a large data set. For example, a modern GPU is a large collection of slower co-processors that can simply apply the same computation on different parts of relatively smaller data, but the SPMD parallelism ends up with an efficient way to obtain final solutions (i.e. time to solution is shorter). (Wikipedia).
R programming for Beginners | R programming for data Science
R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. This video is a
From playlist Programming
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Big Data
Introduction to R: Reading and Writing Data
In the real world you'll typically access data that exists outside of R and then read that data into your programming environment to conduct your analysis. R contains a variety of functions, both built-in and available in packages to load in data in a wide variety of formats. In this les
From playlist Introduction to R
Introduction to R: Atomic Data Types
In this lesson we cover the basic atomic data types available in R including doubles, integers, logicals and characters. This is lesson 3 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below: Introduction to R:
From playlist Introduction to R
Data Types in R - Introduction to R Programming - Part 2
Itโs really important to know your main data types so you can check what kind of values youโre working with when modeling data, or when casting it as a certain data type. Learn how to check numeric data types from integers, to floating-point numbers, to negative and positive numbers, as we
From playlist Introduction to R Programming
You can go a long way in R doing data science using functions built into the base language or available in packages, but sooner or later you'll probably need to write custom code to perform an operation that is not available in a prepackaged function. In this lesson, we learn how to create
From playlist Introduction to R
Introduction to R Programming for Excel Users
R programming is rapidly becoming a valuable skill for data professionals of all stripes and a must-have skill for aspiring data scientists. Adding R programming to your data analyst skillset allows you to leverage powerful data visualizations, statistical analyses, and even machine learni
From playlist Short Crash Courses for Data Science & Data Engineering
Introduction to R: Working with Text Data
Text data, also known as character data in R is a common data type that often requires significant preprocessing and data cleaning before you can use it for analysis and modeling. Text data is often referred to as string data (character strings) in other programming languages. In this less
From playlist Introduction to R
In this lesson we learn about the most basic compound data type in R: the vector. Vectors in R are essentially lists of values of the same basic data type. R vectors are great for data analytics and data science because many common functions are built to operate on entire vectors all at on
From playlist Introduction to R
Introduction to Data Science with R | Data Science Tutorial | Edureka | Data Science Live - 4
๐ฅEdureka Data Science Training: https://www.edureka.co/data-science-r-programming-certification-course This Edureka video on what is Data Science will help you understand the various aspects of Data Science using R. ๐ดSubscribe to our channel to get video updates. Hit the subscribe butto
From playlist Edureka Live Classes 2020
Data Science Jobs, Skills and Salary | Data Science Career | Data Science Training | Simplilearn
๐ฅ Enroll For Simplilearn's Data Science Job Guarantee Program: https://www.simplilearn.com/data-science-course-placement-guarantee?utm_campaign=DataScienceJobSkillsOct18&utm_medium=DescriptionFirstFold&utm_source=youtube Data Science as a field is expanding rapidly, with companies looking
Introduction to Random Forest in R | Data Science Training | Edureka | Data Science Live - 3
๐ฅEdureka Data Science Training: https://www.edureka.co/data-science-r-programming-certification-course This Edureka Random Forest tutorial will help you understand all the basics of the Random Forest machine learning algorithm. This tutorial is ideal for both beginners as well as professi
From playlist Edureka Live Classes 2020
Python vs R vs SAS | R, Python And SAS Comparison | What I Should Learn In 2021? | Simplilearn
๐ฅExplore Our Free Courses: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=Python&utm_medium=DescriptionFirstFold&utm_source=youtube This video on Python vs R vs SAS will help you understand the fundamental difference between the three most popularly used programming l
From playlist R Programming For Beginners [2022 Updated]
Introduction to Data Science | Data Science For Beginners | Edureka | Data Science Rewind - 1
๐ฅEdureka Data Science Training: https://www.edureka.co/data-science-r-programming-certification-course This Edureka video on Introduction to Data Science will help you understand the various aspects of Data Science. ๐ดSubscribe to our channel to get video updates. Hit the subscribe button
From playlist Edureka Live Classes 2020
Data Science Tutorial for Beginners | What is Data Science | Edureka | Data Science Live -1
๐ฅEdureka Data Science Training: https://www.edureka.co/data-science-r-programming-certification-course This Edureka video on what is Data Science will help you understand the various aspects of Data Science. ๐ดSubscribe to our channel to get video updates. Hit the subscribe button above:
From playlist Edureka Live Classes 2020
Top Big Data Technologies | Big Data Tools Tutorial | Big Data Hadoop Training | Edureka Rewind
๐ฅ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐ข๐ ๐๐๐ญ๐ ๐๐๐๐จ๐จ๐ฉ ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐ซ๐๐ข๐ง๐ข๐ง๐ ๐๐จ๐ฎ๐ซ๐ฌ๐ (๐๐ฌ๐ ๐๐จ๐๐: ๐๐๐๐๐๐๐๐๐) : https://www.edureka.co/big-data-hadoop-training-certification This Edureka video on Big Data Technologies will provide you in-depth knowledge on Big Data Tools. This video will help you understand different t
From playlist Big Data Hadoop Tutorial Videos | Edureka
Data Scientist Jobs, Salary & Skills | Data Scientist Resume | Data Science | Edureka | Rewind - 3
๐ฅEdureka Data Scientist Master Program: https://www.edureka.co/masters-program/data-scientist-certification This session on Data Scientist Jobs, Salary & Skill will help you understand the demand and the growth of a Data Scientist and their impact on the business world. ๐น Check our compl
From playlist Edureka Live Classes 2020
Complete Roadmap to become a Data Scientist | Data Scientist Career | Learn Data Science | Edureka
๐ฅ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐๐ญ๐ ๐๐๐ข๐๐ง๐๐ ๐ฐ๐ข๐ญ๐ก ๐๐ฒ๐ญ๐ก๐จ๐ง ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐จ๐ฎ๐ซ๐ฌ๐: https://www.edureka.co/data-science-python-certification-course (Use code ๐๐๐๐๐๐๐๐๐ for a flat 20%off on all trainings) This video on 'Data Scientist Roadmap' will help you understand who is a Data Scientist, Data Scientist Roles and
From playlist Data Science Training Videos
Predictive Analysis Tutorial | Predictive Analytics Using R | Data Science | Edureka | Rewind -2
๐ฅEdureka Data Science Certification using R: https://www.edureka.co/data-science-r-programming-certification-course This Edureka video on "Predictive Analysis Tutorial", will help you learn about how predictive analytics works and how it can be implemented using R to solve real-world prob
From playlist Edureka Live Classes 2020
Should You Learn R for Data Science?
In this video I talk about if you should learn R for Data Science. In general, R is most useful in medical and research fields. R is good for building interactive visuals (R Shiny), and may have some modules that are superior to those in Python. On the other hand. Python has better docu
From playlist Data Science