Case Study

Classifying ‘Spam’ Text using Exploratory Data Analysis

Scammers send fake messages and try to steal your personal data and gain access to your bank accounts, emails etc. It is important to identify spam texts and avoid them.

Exploratory Data Analysis On Spam Text Classification
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

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    Duration: Approximately 3 hours

Case Overview

  • The case familiarizes the learner about the concepts of Natural Language Processing and text analytics to identify irrelevant and unwanted spam texts to safeguard their privacy and stay away from scammers.
  • Working understanding of text preprocessing techniques to remove noise and convert the textual data to machine understandable format.
  • Learn how to apply EDA techniques such as Word Cloud on Text data to identify the most frequently occurring words in spam messages and their significance.
  • The case helps the learner to analyze the importance of each word by implementing TF-IDF technique, along with word association that acts a vital insight to identify spam texts.

What’s included

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Skills You Will Learn

Text Pre-Processing

Text Visualization

Information Retrieval Through Text Analytics

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