Fake News Detection with Machine Learning

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Coursera Project Network
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En este proyecto guiado, tú:

Create a pipeline to remove stop-words ,perform tokenization and padding.

Understand the theory and intuition behind Recurrent Neural Networks and LSTM

Train the deep learning model and assess its performance

Clock2 hours
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this hands-on project, we will train a Bidirectional Neural Network and LSTM based deep learning model to detect fake news from a given news corpus. This project could be practically used by any media company to automatically predict whether the circulating news is fake or not. The process could be done automatically without having humans manually review thousands of news related articles. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

Python ProgrammingMachine LearningNatural Language ProcessingArtificial Intelligence(AI)

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Understand the Problem Statement and business case 

  2. Import libraries and datasets

  3. Perform Exploratory Data Analysis

  4. Perform Data Cleaning

  5. Visualize the cleaned data

  6. Prepare the data by tokenizing and padding

  7. Understand the theory and intuition behind Recurrent Neural Networks

  8. Understand the theory and intuition behind LSTM

  9. Build and train the model

  10. Assess trained model performance

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso



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