GOAL: Classify emails as spam or not-spam on the basis of the message.

DATASET: E-Mail classification NLP

WHAT I HAD DONE:

I have started with simple Exploratory Data Analysis(EDA), looked for some null or duplicate vales. Then splited the training and testing dataset using sklearn. Then I implemented different models to classify the message as spam or not-spam.

MODELS USED:

1. Naive Bayes (Multinominal)
2. Random Forest Classifier
3. XG Boost Classifier

LIBRARIES NEEDED:

1. Numpy
2. Pandas
3. Sklearn

CONCLUSION:

Naive Bayes (Multinominal) Training Set Accuracy	Naive Bayes (Multinominal) Testing Set Accuracy