Predictive text modeling. The application was built as a part of the capstone project for the Coursera Data Science specialization course held by professors of John Hopkins University in cooperation with Swiftkey.

This is the milestone report for the Exploratory Analysis section of the Coursera Data Science Capstone project. The goal of this capstone project is to analyze a large corpus of text documents to discover the structure in the data and how words are put together. By cleaning and analyzing text data, I will then build a predictive text model.

This is another mini project I carried out to not only display my data mining and visualization skills but to also show my abilities to gather and manipulate data from multiple sources. Due to the limitations Twitter has set on API tweet pulls and date range, I was able to extract 1340 tweets generated within the last 7 days; from the date of tweet pull. I performed this analysis using the R Programming Language.

This is my first attempt at a kaggle dataset. Decided to give it a try to test my data exploratory abilities

These passenger datasets contain data pertaining to customer demographics and satisfaction with Airport facilities, services, and initiatives. The current data was collected in May 2015 through interviews with 2,958 customers in each of SFO’s terminals and boarding areas.

Based on 'ToothGrowth' dataset in RStudio

Data Analysis based on Weather Events recorded by U.S. National Oceanic and Atmospheric Administration's (NOAA)

MPG Dataset Transformation

MPG Dataset Transformation: Rental Car Options