Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

E-mail SPAM detection model using Multinomial Naive Bayes algorithm[EXE] #194

Open
darpan-2001 opened this issue Oct 8, 2022 · 3 comments

Comments

@darpan-2001
Copy link

Learning Goals

Naive Bayes algorithm, text feature extraction, sklearn pipeline object.

Exercise Statement

Create an e-mail spam detection model.

Prerequisites

Basic understanding of Naive Bayes algorithm, Python and scikit-learn basics.

Data source/summary:

Dataset if obtained from Kaggle. Data consists of email messages, already labeled as spam or ham.
Link of dataset: https://www.kaggle.com/code/mfaisalqureshi/email-spam-detection-98-accuracy/data

(Optional) Suggest/Propose Solutions

I have the solution ready implemented with Multinomial Naive Bayes algorithm, will be happy to create pull request to include the exercise solution.

@lucifertrj
Copy link

I will take this one, could you assign me this project @darpan-2001?

@DhruvSanghvi2002
Copy link

I would love to solve this challenge ,kindly assign me this issue @darpan-2001

@Adarshh9
Copy link

Adarshh9 commented Oct 9, 2023

can you assign me this issue?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

4 participants