Identifying important keywords in job postings is a pivotal step towards writing applicable resumes and cover letters. One method to determine the importance of individual words in a corpus of texts is by calculating the term frequency -- inverse document frequency for every word in the corpus. In this project I perform TF-IDF on a small corpus of job descriptions for positions that I've applied to in order to identify prominent keywords in this collection.
michaelgrn/LinkedinTFIDF
A small project designed to evaluate the TFIDF values extracted from Linkedin job postings.
Jupyter Notebook