A useful machine learning script when sending out hundreds of job applications per week. Filters all rejection emails and organizes them in a live Google Sheets spreadsheet.
- Parses all unread emails every 30 minutes within a Gmail account.
- Determines if each email is a rejection or non_rejection using the machine learning classifier.
- If a rejection email is found:
- move email to the "Rejection" inbox
- update the rejection spreadsheet using the company name, email body, and date rejected
- If non_rejection email is found:
- move email to the "Checked" inbox
- continue checking emails
- View notebook at https://www.kaggle.com/sethpoly/detect-reject-emails
- View dataset at https://www.kaggle.com/sethpoly/application-rejection-emails
- Developed a model to classify emails as either "rejection" or "non-rejection"
- Implemented Naive Bayes classifier
Filters unread emails every 30 minutes, and categorizes them as rejection/non_rejection:
If rejection email is found, connect to Google Sheets API and create an entry in the spreadsheet containing the company that rejected me, the email sent, and date of rejection.
Python, imaplib, pandas, sklearn, Google Drive API