A Python tool for comprehensive resume analysis. This project provides functionalities to clean, process, and extract insights from resumes, including n-gram generation, topic detection, word cloud visualization, statistical analysis, and optional network visualization.
- Full Text Cleaning: Rigorous cleaning has been done to enhance the data quality.
- Bi-grams and Tri-grams Generation: Capturing subtle relationships between words.
- Topic Detection: Uncovering prevalent themes within the resume.
- Word Cloud: Visualizing the most prominent words for quick insights.
- Main Statistics: Quantitative metrics providing insights into the textual content.
- Network Generation: Illustrating word connections through network graphs.
- pandas (version 1.3.3): Data manipulation library.
- nltk (version 3.6.3): Natural Language Toolkit for text processing.
- gensim (version 4.2.0): Library for topic modeling and document similarity.
- wordcloud (version 1.8.1): Library for creating word clouds.
- networkx (version 2.6.3): Library for network analysis.
- matplotlib (version 3.4.3): Plotting library.
- main.py: Contains the Python code for the resume analysis tool.
- resumes.csv: Sample CSV file containing resume data for testing.
For detailed findings and insights from the analysis, refer to the report attached. The report includes information on the resumes under analysis, steps involved in the analysis, and a comparative analysis of multiple resumes.