Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/manasvigoyal/gmail-classification
Extract Emails from Gmail account, convert to Excel file and classify using various classification algorithms.
https://github.com/manasvigoyal/gmail-classification
beautifulsoup classification email-classification excel gmail jupyter-notebooks machine-learning matplotlib numpy pandas python scikit-learn seaborn
Last synced: 25 days ago
JSON representation
Extract Emails from Gmail account, convert to Excel file and classify using various classification algorithms.
- Host: GitHub
- URL: https://github.com/manasvigoyal/gmail-classification
- Owner: ManasviGoyal
- License: gpl-3.0
- Created: 2021-06-28T10:24:35.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-07-30T23:37:50.000Z (over 3 years ago)
- Last Synced: 2024-07-30T18:49:47.418Z (3 months ago)
- Topics: beautifulsoup, classification, email-classification, excel, gmail, jupyter-notebooks, machine-learning, matplotlib, numpy, pandas, python, scikit-learn, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 861 KB
- Stars: 15
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Gmail Extraction and Classification
## :e-mail: Gmail Extractor
Extracts emails from Gmail from 'Inbox' and 'Spam' folders in .txt format. Then converts each folder to Excel files. Adds 'spam' and 'non-spam' Labels and 1/0 Label_Numbers. Merges both Excel files into one and shuffles them.Working of Code
**NOTE**: enable 'Less Secure App' access for the code to work
https://myaccount.google.com/lesssecureapps## :mailbox_with_mail: Gmail Classification
### Main steps to build a classifier -
### 🛠️ Machine Learning Models Used -
- Logistic Regression
- Support Vector Machine (Linear)
- Support Vector Machine (RBF)
- K Nearest Neighbor
- Decision Tree Classifier
- Random Forest Classifier
- Multinomial Naïve Bayes### Python Libraries
![NumPy](https://img.shields.io/badge/-NumPy-05122A?style=flat&logo=NumPy)
![Pandas](https://img.shields.io/badge/-Pandas-05122A?style=flat&logo=Pandas)
![Matplotlib](https://img.shields.io/badge/-Matplotlib-05122A?style=flat&logo=Matplotlib)
![Seaborn](https://img.shields.io/badge/-Seaborn-05122A?style=flat&logo=Seaborn)
![NLTK](https://img.shields.io/badge/-NLTK-05122A?style=flat&logo=NLTK)
![Scikit-Learn](https://img.shields.io/badge/-ScikitLearn-05122A?style=flat&logo=scikit-learn)\
![BeautifulSoup](https://img.shields.io/badge/-BeautifulSoup-05122A?style=flat&logo=BeautifulSoup)
![imaplib](https://img.shields.io/badge/-Imaplib-05122A?style=flat&logo=imaplib)
![OS](https://img.shields.io/badge/-OS-05122A?style=flat&logo=os)
![RE](https://img.shields.io/badge/-RE-05122A?style=flat&logo=re)
![codecs](https://img.shields.io/badge/-Codecs-05122A?style=flat&logo=codecs)
![getpass](https://img.shields.io/badge/-GetPass-05122A?style=flat&logo=getpass)
![email](https://img.shields.io/badge/-Email-05122A?style=flat&logo=email)