-
The Resume Categorizer is a machine learning project designed to classify resumes into predefined categories such as Software Engineer, Data Scientist, Marketing, etc. The project utilizes Natural Language Processing (NLP) techniques, specifically TF-IDF vectorization, and label encoding for the machine learning model to predict the category of a given resume.
-
The tool can be used by recruiters or HR teams to automatically filter and categorize resumes based on content, improving the efficiency of the hiring process.
- Text Preprocessing: The resumes are preprocessed to remove irrelevant details such as stopwords, special characters, and numbers.
- TF-IDF Vectorization: The resume text is converted into a matrix of TF-IDF features to represent the resumes as numerical vectors.
- Label Encoding: Categories are encoded as integers, which are fed into machine learning models for classification.
- Resume Categorization: The model categorizes resumes into their respective fields such as Data Science, Web Development, Marketing, etc.