This codebase is for the talk:
Title: Machine Learning with Ruby
Abstract:
I will discuss ways to make sense out of data. Specifically:
* Using Classification, Clustering and Recommendation algorithms
* and a demo
Requirements
* A basic understanding of Ruby Programming Language
* Basic mathematics: Probability and Statistics
Add this line to your application's Gemfile:
gem 'rubyml'
And then execute:
$ bundle
Or install it yourself as:
$ gem install rubyml
When using the bundler
$ bundle install
$ bundle update -V
$ bundle exec news_classifier.rb
When using only gem command
$ gem build *.gemspec; gem install --local -V rubyml-0.0.1.gem
$ news_classifier.rb
To test
$ bundle install
$ bundle update -V
$ bundle exec rake test
- Fork it ( http://github.com/tuxdna/rubyml/fork )
- Create your feature branch (
git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create new Pull Request
Machine Learning with Ruby
To create presentation first install landslide via pip:
$ sudo yum install -y python-pip
$ pip-python install landslide
Create the presentation:
$ cd talk/
$ landslide rubyml-talk.md --relative --copy-theme -i
Open it in your favorite browser:
$ firefox presentation.html
Update the presentation while you are still working on it:
Install inotify-tools on Ubuntu:
$ sudo aptitude install inotify-tools
Use inotifywait to invoke rebuild on every change
$ while inotifywait -e close_write rubyml-talk.md ; do landslide rubyml-talk.md --relative --copy-theme -i; done