Tag Archives: R programming

Code Recipe: How to Calculate Twitter Sentiment Using AlchemyAPI with Python


via How to Calculate Twitter Sentiment Using AlchemyAPI With Python | AlchemyAPI.

One of the most common applications of text analysis is sentiment analysis on social media posts, with Twitter being a common data source. Gathering Twitter sentiment data isn’t actually too difficult once you have the right tools. This tutorial will walk you through the steps required to connect to the Twitter API, search for Tweets, and perform sentiment analysis using AlchemyAPI’s sentiment API.

Here, we will show you how to get the data, calculate sentiment, and do some basic analysis and visualization of your results. By the end of this guide you’ll be ready to expand on this simple application to create an extremely powerful solution. While this tutorial uses Python and R, it should be easy to follow a similar methodology to recreate this application in the programming language(s) of your choice.

Machine Learning of Machines with R


A short talk with scripts, data and notes on using machine learning with R. Presented to the Dublin R Usergroup on March 19 2015

Neural networks in R


via Neural networks in the R – “Art of Data”.

In this example, we use NNET Package and available based on the UCI repository of   Bank Marketing Data Set .

R: Removing for loops


via R: Removing for loops at Mark Needham.

In my last blog post I showed the translation of a likelihood function from Think Bayes into R and in my first attempt at this function I used a couple of nested for loops.

Video: RNeo4j Graphs


RNeo4j combines the power of a Neo4j graph database with the R statistical  programming language to easily build predictive models based on connected data. From calculating the probability of friends of friends connections to plotting an adjacency heat map based on graph analytics, the RNeo4j package allows for easy interaction with a Neo4j graph database. Listen in as Nicole White, Data Scientist at Neo4j, presents how to utilize the RNeo4j package.