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Analysis of SMS tagged 5K+ messages collection to classify them as spam or ham. Used Natural Language Processing techniques to transform data into an understandable format.

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SMS_spam_classification

Overview:

The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of SMS messages in English of 5,574 messages, tagged acording being ham (legitimate) or spam.

Objective:

To classify the messages as Spam or Non-Spam, using Natural Language Processing techniques for data processing.

Language:

Python

Libraries:

  1. Numpy
  2. Pandas
  3. Matplotlib
  4. scikit-learn
  5. Seaborn
  6. nltk

Machine Learning:

  1. Gaussian Naive Bayes
  2. Decision Tree Classification
  3. Random Forest Classification

Author:

Ritvika Nandi

About

Analysis of SMS tagged 5K+ messages collection to classify them as spam or ham. Used Natural Language Processing techniques to transform data into an understandable format.

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