Industry Use Case

Predictive Modeling for Fake News Detection Using NLP

This project provides foundational knowledge to apply different NLP techniques and perform predictive modeling in the context of identifying fake news

Predictive Modelling for Fake News Detection Using NLP Techniques
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

  • Asset 1
    Duration: Approximately 3 hours

Course Overview

  • Currently, increase in unregulated to access has lead to spread of different fake news causing panic in society. Identifying whether a piece of news is authentic or fake becomes challenging for a usual person.
  • Like many other sectors, the field of NLP has found major applications in tackling this challenge. The first step involves appropriate processing of the text data and insight gathering based on which an appropriate model can be used to determine its authenticity.
  • Learn the fundamentals of text analytics and how to apply efficient NLP techniques on any text to predict whether it is fake news.

What’s included

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Lifetime Access

Access this case study for life once completed

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Flexible Scheduling

Start learning online immediately, at your own pace

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Desktop Only

We recommend accessing this case study via desktop

Skills you will learn

Text Preprocessing

Univariate Feature Visualization

Word Cloud Visualization

Association Rule

TF-IDF

Classification Model Building

Model Evaluation and Comparison

Associated Learning Tracks

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