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Naive Bayes algorithm, text feature extraction, sklearn pipeline object.
Create an e-mail spam detection model.
Basic understanding of Naive Bayes algorithm, Python and scikit-learn basics.
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
I have the solution ready implemented with Multinomial Naive Bayes algorithm, will be happy to create pull request to include the exercise solution.
The text was updated successfully, but these errors were encountered:
I will take this one, could you assign me this project @darpan-2001?
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I would love to solve this challenge ,kindly assign me this issue @darpan-2001
can you assign me this issue?
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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.
The text was updated successfully, but these errors were encountered: