This is a quick and dirty analysis of my learning data from Sep 17 to Nov 17 on Linkedin/Lynda Learning platform. Some text processing, term document matrix or document term matrix, N-grams, Wordclouds, Find associative words...

Around the world, people are spending an increasing amount of time on their mobile devices for email, social networking, banking and a whole range of other activities. But typing on mobile devices can be a serious pain. SwiftKey, our corporate partner in this capstone, builds a smart keyboard that makes it easier for people to type on their mobile devices. One cornerstone of their smart keyboard is predictive text models. When someone types: I went to the the keyboard presents three options for what the next word might be. For example, the three words might be gym, store, restaurant. In this capstone you will work on understanding and building predictive text models like those used by SwiftKey.

Getting Started with R Programming

Work in progress: Response Modeling - Credit Scoring using Machine Learning

Human Activity Monitoring Data Analysis