Detection and Classification of Fake news using Convolutional Neural networks

location_city Bengaluru schedule Aug 31st 02:55 - 03:15 PM place Grand Ball Room 1 people 108 Interested

The proliferation of fake news or rumours in traditional news media sites, social media, feeds, and blogs have made it extremely difficult and challenging to trust any news in day to day life. There are wide implications of false information on both individuals and society. Even though humans can identify and classify fake news through heuristics, common sense and analysis there is a huge demand for an automated computational approach to achieve scalability and reliability. This talk explains how Neural probabilistic models using deep learning techniques are used to classify and detect fake news.

This talk will start with an introduction to Deep learning, Tensor flow(Google's Deep learning framework), Dense vectors (word2vec model) feature extraction, data preprocessing techniques, feature selection, PCA and move on to explain how a scalable machine learning architecture for fake news detection can be built.

 
 

Outline/Structure of the Talk

The outline would be in the following order:

  • Why identification of fake news is relevant in today's biased world.
  • Showcasing a neural network architecture(CNN) built to solve the problem at scale.
  • Compare with other state of art techniques developed for this problem.
  • Challenges faced identifying fake articles through Machine learning methodologies.

Learning Outcome

  • Understand the role of Deep learning models in Text mining and classification
  • Build scalable architecture in machine learning applications and deploy it Live

Target Audience

Individuals interested in NLP, Text mining,Data mining and Deep learning approaches for text classification

Prerequisites for Attendees

Understanding of Deep learning, Convolutional neural networks and Text classification.

schedule Submitted 2 years ago

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