Computer Tips - Programming, Cybersecurity and Tech Tutorials

C and C++: The major difference between C and C++ is that C is a procedural programming language and does not support classes and objects, while C++ is a combination of both procedural and object oriented programming language; therefore C++ can be called a hybrid language. C: C was developed by Dennis Ritchie between 1969 and 1973 at AT&T Bell Labs. When compared to C++, C is a subset of C++. C supports procedural programming paradigm for code development. In C (because it is a procedural programming language), data and functions are separate and free entities.

Full Stack Development: The term full-stack means developers who are comfortable working with both back-end and front-end technologies. To be more specific, it means that the developer can work with databases, PHP, HTML, CSS, JavaScript and everything in between, also, venturing as far as converting Photoshop designs to front-end code. (Ref.: https://www.sitepoint.com/full-stack-developer/ ) MEAN Stack: MEAN is a framework for an easy starting point with MongoDB, Node.js, Express, and AngularJS based applications. It is designed to give you a quick and organized way to start developing MEAN based web apps with useful modules like Mongoose and Passport pre-bundled and configured. We mainly try to take care of the connection points between existing popular frameworks and solve common integration problems. (Ref.: http://learn.mean.io/ ) Online Certification Courses (MOOCs) and Tutorials: https://www.udacity.com/course/full-stack-web-developer-nanodegree--nd004 h...

What is Anaconda? Anaconda is the leading open data science platform powered by Python. The open source version of Anaconda is a high performance distribution of Python and R and includes over 100 of the most popular Python, R and Scala packages for data science. Ref.: https://www.continuum.io/downloads The error reads as below: Traceback (most recent call last): File "C:\Anaconda2\Lib\_nsis.py", line 164, in <module> main() File "C:\Anaconda2\Lib\_nsis.py", line 150, in main   mk_menus(remove=False) File "C:\Anaconda2\Lib\_nsis.py", line 94, in mk_menus   err("Traceback:\n%s\n" % traceback.format_exc(20)) IOError: [Errno 9] Bad file descriptor

What is Git? Git is a version control system that is used for software development and other version control tasks. As a distributed revision control system it is aimed at speed, data integrity, and support for distributed, non-linear workflows. Git was created by Linus Torvalds in 2005 for the development of the Linux kernel, with other kernel developers contributing to its initial development. Read more about Git: https://en.wikipedia.org/wiki/Git_(software) What is GitBlit? Gitblit is an open-source, pure Java stack for managing, viewing, and serving Git repositories. It's designed primarily as a tool for small workgroups who want to host centralized repositories. Read more about GitBlit: http://gitblit.com/

I have installed shiny server on Ubuntu 14.04 LTS running under a VM. This post is a collection of commands that I had used for setup. Note that if you want to use shiny server on LAN then use Bridged Network Adapter. On VM you can access the shiny server via localhost:3838 and on remote machines, you can use IP-address:3838 to open it. You can host your shiny app in the /srv/shiny-server/ directory. You can go to /etc/shiny-server/shiny-server.conf to change default configurations like you can change port with listen <port number>; in server {} module. $ sudo sh -c 'echo "deb http://cran.rstudio.com/bin/linux/ubuntu trusty/" >> /etc/apt/sources.list' $ sudo gpg --keyserver keyserver.ubuntu.com --recv-key E084DAB9 $ sudo gpg -a --export E084DAB9 | sudo apt-key add - $ sudo apt-get update $ sudo apt-get -y install r-base $ sudo su - -c "R -e \"install.packages(c('shiny','shinyjs','shinydashboard','...

TEXT (.txt) This working script was tested on R 3.2.5 . Code is adapted from https://github.com/gimoya/theBioBucket-Archives/blob/master/R/txtmining_pdf.R . It reads a text file, processes it to remove unnecessary words and plots it. Code: library(tm) library(wordcloud) library(Rstem) filetxt <- "C:\\Users\\310211146\\Documents\\Other\\May_Report.txt" txt <- readLines(filetxt) txt <- tolower(txt) txt <- removeWords(txt, c("\\f", stopwords())) corpus <- Corpus(VectorSource(txt)) corpus <- tm_map(corpus, removePunctuation) tdm <- TermDocumentMatrix(corpus) m <- as.matrix(tdm) d <- data.frame(freq = sort(rowSums(m), decreasing = TRUE)) d$stem <- wordStem(row.names(d), language = "english") d$word <- row.names(d) d <- d[nchar(row.names(d)) < 20,] agg_freq <- aggregate(freq ~ stem, data = d, sum) agg_word <- aggregate(word ~ stem, data = d, function(x)   x[1]) d <- cbind(freq...

If you are new to R or wants to enhance your basic skills in R and wondering where to get started provided there is lots of free material available online then you have come to right place. I have presented 5 video tutorials that is more than enough to get you started with R and will push you in direction of excelling R. 1. What is R and How to install it? 2. What are data types and variables in R?