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In this project, we are going to create a machine learning model by using NLP that will classify SMS messages as either "ham" or "spam". A "ham" message is a normal message sent by a friend. A "spam" message is an advertisement or a message sent by a company.

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SaumyaSubham/spam_classifier

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spam_classifier

In this project, we are going to create a machine learning model by using NLP that will classify SMS messages as either "ham" or "spam". A "ham" message is a normal message sent by a friend. A "spam" message is an advertisement or a message sent by a company.

We would create a function called predict_message that takes a message string as an argument and returns a list. The first element in the list should be a number between zero and one that indicates the likeliness of "ham" (0) or "spam" (1). The second element in the list should be the word "ham" or "spam", depending on which is most likely.

For this project, we will use the SMS Spam Collection dataset. The dataset has already been grouped into train data and test data.

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In this project, we are going to create a machine learning model by using NLP that will classify SMS messages as either "ham" or "spam". A "ham" message is a normal message sent by a friend. A "spam" message is an advertisement or a message sent by a company.

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