I created this Shiny App in 2014 based on my research on consumer behavior and infrastructure analysis. The backend of this model is based on a multinomial logistic regression algorithm, which takes in consumer characteristics, vehicle attributes, and predicts the probability of the consumer purchasing a vehicle technology. The App gives the top 3 optimal choices for the consumer.
This was done as part of the Coursera Data Science Specialization project. Based on the corpus of text data given, n-grams were created. The tool predicts the next word in real-time based on the word chains given in the input. Model details are given under the 'Model' tab in the app.
Click here to play with the next word prediction tool.
This is a simple random forest classification done in R, to identify the conversion of a website.