Skip to content

Implementation of natural language processing, supervised and unsupervised machine learning methods for classifying events around the US to automate a travel start-up's recommendation pipeline. Includes interactive command line tool.

Notifications You must be signed in to change notification settings

arishty/travel-rec-automation

Repository files navigation

NYCDSA Capstone Project

In this project, we worked with a US travel recommendation startup, automating processes such as categorizing events in the US with supervised and unsupervised learning methods.

  • To view the finalized documented notebook of our work, please refer to Event_Processing_Models_With_Thresholds_pickled.ipynb.

  • To use our CLI tool, one can navigate to the LTD_model_deploy directory and run "python model_deploy.py -d [insert event description] -v [insert 0,1, or 2]" to output label predictions.

  • Use -v 0 to only output the label predictions and corresponding probabilities
  • Use -v 1 to output the label predictions and probabilities as well as the original event description enterred
  • Use -v 2 to output all of the above, as well as the preprocessed set of words that the classifier evaluates

About

Implementation of natural language processing, supervised and unsupervised machine learning methods for classifying events around the US to automate a travel start-up's recommendation pipeline. Includes interactive command line tool.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published