Goodreads Analysis
https://shanfu.shinyapps.io/shiny_books/
Shiny app analyzing book genre popularity
- R, Shiny, ggplot2, R markdown, knitr, Ruby, JavaScript
- Visualize genre popularity over time, by gender, age group, and location
followmap
http://followmap.herokuapp.com
D3 visualization of Twitter followers and friends
- Ruby, Rails 4, D3js, topojson
- Visualize followers and friends of any Twitter user on a global map
geofeelings
http://geofeelings.herokuapp.com
D3 real time visualization of global Twitter sentiment
- Ruby, Rails 4, D3js, topojson
- Sentiment analysis using customized AFINN-111 lexicon
- Enter a search term to see geofeelings mine Twitter, analyze tweet sentiment and place tweets on a global map colored by attitude all in real(ish) time
bagRboostR
An R Package for ensemble bagging and boosting classifiers
- A set of ensemble classifiers for multinomial classification problems
- The bagging function is the implementation of Breiman’s ensemble as described by Opitz and Maclin (1999)
- The boosting function is the implementation of Stagewise Additive Modeling using a Multi-class Exponential loss function (SAMME) created by Zhu et al (2006)
- Each ensemble classifier returns a character vector of predictions for a given test set
- bagRboostR Manual
Read Me Read You
A Ruby on Rails application for the writing community
- A community for sharing writing and critiques
- Manuscript analysis including:
- Lexical Density
- Gunning Fog Index
- Flesch Reading Ease
- Flesch-Kincaid Grade Level
- Word and Sentence counts
- Unique and Commonly Used Word Analysis
- Word Grouping Analysis
- Sentence Structure Analysis
- More details and source code can be found at the RMRY github repo
Talent Driven Development
http://talentdrivendevelopment.com
A Ruby on Rails application for technical talent management
- Helps technical talent with the problem of having to weed through tons of unwanted recruitment emails when looking for a new opportunity
- Allows technical talent the opportunity to choose a specialized agent for representation
- Agents find interviews and negotiate offers for the talent they represent
- Agents earn badges to enhance their reputation based on performance
- The better the performance (acceptable interviews, accepted offers, etc) the more talent an agent may represent
- Ruby 1.9.3
- Rails 3.2.3
- Front end created using Haml and Sass
- Tested using rspec and factory girl
- Authentication system using devise
- Search using sunspot and Solr
- Recurring tasks using whenever
- Image management using paperclip
- More details and source code can be found at the TDD github repo
- Specialties:
- Data Science
- Data Visualization
- Machine Learning
- Predictive Analytics
- R
- Ruby on Rails
- Github: