Detect Fake News in Python with Tensorflow

von
Coursera Project Network
In diesem angeleitetes Projekt werden Sie:

Collect and prepare text-based training and validation data for classifying text

Perform term frequency–inverse document frequency vectorization on text samples to determine similarity between texts for classification

Train a Deep Neural Network to classify Fake News articles

Clock2 hours
IntermediateMittel
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

"Fake News" is a word used to mean different things to different people. At its heart, we define "fake news" as any news stories which are false: the article itself is fabricated without verifiable evidence, citations or quotations. Often these stories may be lies and propaganda that is deliberately intended to confuse the viewer, or may be characterized as "click-bait" written for monetary incentives (the writer profits on the number of people who click on the story). In recent years, fake news stories have proliferated via social media, partially because they are so readily and widely spread online. Worse yet, Artificial Intelligence and natural language processing, or NLP, technology is ushering in an era of artificially-generated fake news. Both types of fake news are detectable with the use of NLP and deep learning. In this project, you will learn multiple computational methods of identifying and classifying Fake News. 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.

Kompetenzen, die Sie erwerben werden

  • Tensorflow
  • Python Programming
  • Natural Language Processing
  • Fake News Detection

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  1. Introduction to Fake News and it's Effects on Society

  2. Collecting and Preparing Data for Text Classification

  3. Comparing Text with TF-IDF Vectorization

  4. Source Checking and Claim Matching

  5. Deep Learning Detection with Tensorflow

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.

Häufig gestellte Fragen

Häufig gestellte Fragen

Haben Sie weitere Fragen? Besuchen Sie das Learner Help Center.