The goal of the project is to build a classification model that will classify any new topic submission to the adequate category ( API, Account Server Management, Chat, Mobile, Merchandise, Other, Overlay and Game Store).
Jupyter Notebook: Capstone Project 2- E2E Classification Model.ipynb contains code used to transform text data into their numerical representation, then apply supervised learning models that could learn. Tested different scenarios such as removing stopwords, tf-idf.
Technologies Used
- NLP: NLTK, spacy
- Modeling: Logistic Regression, Gradient Boosting and Random Forest
PowerPoint Presentation "Applying NLP to NNN dataset": highglights trends/calls to action from performing EDA, applying the modes and evaluating them.
Capstone Project 2 Final Report: provides detailed explanation on the steps needed to drive this project to completion.