library(knitr)
opts_chunk$set(tidy.opts=list(width.cutoff=60),tidy=TRUE)
rmarkdown::render("/Users/berkorbay/Dropbox/Courses_given/MEF_BDA_503_2017F/Guidelines/example_homework_1.Rmd",output_format="pdf_document")
rmarkdown::render("/Users/berkorbay/Dropbox/Courses_given/MEF_BDA_503_2017F/Guidelines/example_homework_1.Rmd",output_format="html_document")
  1. Which Programming Language is Better for DataScience?

It is a useful article for beginners to the data science, especially those that will start in the field and looking for a language. Python or R? We have started to learn both Python and R but it is better to be a master in one than continue with others. This article is explaining differences of both languages with advantages and disadvantages.

2.R’s Remarkable Growth

This article is showing the increase of R and Python languages in years with reasons. We can see that both languages growig paralelly acc to requirements and developments. I liked the article to see the growth with comparisons.

3.Awesome R

A curated list of awesome R packages and tools. It is really amazing webside for beginners to search tools of R and all other useful packages and sources.

4.38 Seminal Articles Evert Data Scientist Should Read

All articles are in a different subjecxts but all about data science, they will change our perspective.

5.Visualizations with R

Visualization is the most interesting part to see how data looks like, people can interpret visual data easily. It is good to know that visualization is not the hardest part :)