Add User Resumes to Training Data for Improved Model Performance

[sriraamav]

Description:

The resume parsing system can be enhanced by allowing users to submit their resumes for inclusion in the training data. By continuously updating the training dataset with real-world resumes, the system can improve its accuracy and relevance over time, making it better at identifying skills, categories, and parsing resumes from various industries.

Tips for the issue:

• Implement an opt-in mechanism for users to consent to their resumes being used for training.
• Add data anonymization to remove personal and sensitive information from resumes before storing them.
• Update the pipeline to automatically include new resumes in the dataset used for training.
• Consider a method for periodic retraining of the model as new resumes are collected.

To do:

• Ask us to assign the issue.
• Once assigned, you can start working on the task.
• Create a pull request (PR).

Resource:

• Explore techniques for updating machine learning models with new data.
• Review best practices for data anonymization and privacy.

Notes:
The task is assigned on a first-come, first-serve basis, and the contributor must report progress every 3 days to ensure active development.