Slide deck to my text completion/prediction application and report I've created using R and python

Text mining and analytics on data obtained from twitter, blogs and news channels, this project is part of the datascience R specialization capstone project in association with swiftkey

Airquality analysis using plotly

A demonstration on usage of leaflet in R, with custom markers to denote the various locations with hyperlinks to google maps location information

Analyzing the ToothGrowth data in the R datasets package using exploratory analysis and statistical inferences.

Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. I've made a research on various environmental factors/disasters and their effect on various factors such as public health - "INJURIES", "FATALITIES" and economic damage - "PROPDMG", "CROPDMG" and made a top 10 list of "EVTYPES" that stand at top at contributing to damage to communities

Using the kernlab dataset - spam and building a model to classify mails to spam and nonspam using general linear model function

Fine particulate matter (PM2.5) is an ambient air pollutant for which there is strong evidence that it is harmful to human health. In the United States, the Environmental Protection Agency (EPA) is tasked with setting national ambient air quality standards for fine PM and for tracking the emissions of this pollutant into the atmosphere. Approximatly every 3 years, the EPA releases its database on emissions of PM2.5. This database is known as the National Emissions Inventory (NEI). You can read more information about the NEI at the EPA National Emissions Inventory web site.

Air Quality Case Study using the PM2.5 parameter, between the years 1999 and 2012.

Visualizing the nycflights13 dataset using ggplot function

Visualizing the mtcars dataset using lattice plot function

Visualizing the mtcars dataset using ggplot’s qplot function

Studying usage of K-Means Clustering algorithm using R programming

Studying the functioning and usage of Hierarchical Clustering

Principal component analysis (PCA) and singular value decomposition (SVD) usage study