Basic Data Types in R

As part of tutorial series on Data Science with R from Data Perspective, this first tutorial introduces the very basics of R programming language about basic data types in R.

What we learn:
After the end of the chapter, you are provided with R console so that you can practice what you have learnt in this chapter.

Exposing R-script as API

R is getting popular programming language in the area of Data Science. Integrating Rscript with web UI pages is a challenge which many application developers are facing. In this blog post I will explain how we can expose R script as an API, using rApache and Apache webserver.

rApache is a project supporting web application development using the R statistical language and environmentand the Apache web server.

Exploratory data analysis techniques

In my previous blog post I have explained the steps needed to solve a data analysis problem. Going further, I will be discussing in-detail each and every step of Data Analysis. In this post, we shall discuss about exploratory Analysis.

Data Analysis Steps

After going through the overview of tools & technologies needed to become a Data scientist in my previous blog post, in this post, we shall understand how to tackle a data analysis problem.
Any data analysis project starts with identifying a business problem where historical data exists. A business problem can be anything which can include prediction problems, analyzing customer behavior, identifying new patterns from past events, building recommendation engines etc.

Data Analysis Tools

As mentioned in my previous post , in this post I will be listing out the tools, blogs and forums, online courses that I have gathered over the past one year, which I felt necessary in my journey, which will be helpful to my fellow data science aspirants.

Sentiment Analysis using R

Today I will explain you how to create a basic Movie review engine based on the tweets by people using R.

The implementation of the Review Engine will be as follows:

•          Gets Tweets from Twitter
•          Clean the data
•          Create a Word Cloud
•          Create a data dictionary
•          Score each tweet.