Topic Modeling and Text Classification (Linkbal 2019) – AI/ML Engineer
Having as their main business service to customers, the business department of the company deals directly with clients and looks for solutions to avoid bad services. To improve this, I performed a behavioral and user needs model to know what are the top priorities for the customers and hence with this findings the business services can come up with suggested solutions to improve their services. Using the text data removed from our apps questionnaires and user’s ratings I performed a topic to find out what are the biggest topics on our text data, and later perform a text classification of each of the questionnaire and categorize them for the business department to have the top services that need improvement and the types of improvements highly needed. In this project I used also NLP techniques to clean and pre-process the data and used only traditional ML algorithms such as: ● Logistic Regression; ● KNN; ● Random Forest; ● Multinomial Naive Bayes; ● Support Vector Machine; I was able to perform predictions with an accuracy rate of >92%.