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Jordan Hudgens

Machine Learning on Rails

Jordan Hudgens is the CTO and Founder of DevCamp where he leads instruction and curriculum development for all of the DevCamp and Bottega code schools around the US.

As a developer for over the past decade, Jordan has traveled the world building applications and training individuals on a wide variety of topics, including: Ruby development, big data analysis, and software engineering.

Jordan focuses on project driven education, as opposed to theory based development. This style of teaching is conducive to learning how to build real world products that adhere to industry best practices.

Additionally Jordan has published multiple books on programming and computer science, along with developing training curriculum for Learn.co, devCamp, and AppDev on the topics of Ruby on Rails, Java, AngularJS, NoSQL, API development, and algorithms.

Machine Learning on Rails

Machine learning has become pervasive in the development landscape. Several languages and frameworks have become the de facto leaders in the space, with Python and R leading the space with the most exhaustive list of machine learning libraries. However, many of the most popular machine learning libraries are available in Ruby and can be integrated directly into Rails projects. This removes the need to offload machine learning features to outside applications, and that is the focus of this talk. During this time I will supply an introduction to machine learning, including a discussion on what it is, practical uses for it in real world applications, along with the various types of machine learning algorithm options. After that I will walk through how to practically implement machine learning features into Rails applications. The case studies we’ll examine will be: how to analyze a potential baseball player prospect and how to predict when a fleet truck should be retired.