Tag: R Programming

Data Science, R Programming

20 Most Popular R packages

R offers multiple packages for performing data analysis. Apart from providing an awesome interface for statistical analysis, the next best thing about R is the endless support it gets from developers and data science maestros from all over the world. Currently, the CRAN Package repository features 11349 available packages. But the question is which packages are the most popular packages used […]

Data Science, Data Science with Python

Structure of a Data Science Project | Different Phases in Data Science Project

A typical data science project will be structured in a few different phases. There’s roughly five different phases that we can think about in a data science project. Phase 1: Defining A Question The first phase is the most important phase, and that’s the phase where you ask the question and you specify what is it that you’re interested in […]

Data Science, Machine Learning, R Programming

The Most Popular Languages for Data Science and Analytics – 2017

Because this post is about most popular languages for data science, it might be reasonable to first ask, “What is data science?”. Most people are creating hype around data science that data science have focused on the first word: data. They always care about volume and velocity and whatever other buzzwords describe data that is too big for you to […]

Data Science, R Programming

List of Big Companies using R

 The continuous popularity and growth of R Programming Language has been helping data-driven companies succeed for more than a decade. In recent years, almost every industry sees data and analytics as a strategic competitive advantage. And R is the language of choice for many data scientist and data analyst. According to O’Reilly’s 2016 data science salary survey, R was in […]

R Programming

How to Integrate R with Java?

Java is undisputedly a great language for building enterprise solutions, but has miles to scale on the analytics front. Of course, there are effective tools like Weka, whose algorithms could be called from Java codes. Weka is empowered with tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. […]