For each cluster we applied the topic modeling to extract the context and came up with different topics/area that various documents in the corpus consisted of. This analysis gives a great value-add to the business—to understand if there are redundancy in the documentations, to see where they need to improve their documentations, and understand how can it be improved and made more efficient for customers using their products. The right documentation reduced time and money for the business in various ways.
The exposure to the real world data science problem and working with mentors on-site and guiding us throughout the project was a great learning experience; really, it was the most valuable part. The experience adds great value to my resume for my prospect carrier in the field of data science and gives me a sense on how to approach data science problems from scratch. After I graduate, I want to work in the field of data science to contribute and learn more. If everything works well, I might come back for PhD.