Detection & Classification of Fake news using Convolutional Neural Nets
summary
Covers using deep learning—specifically convolutional neural networks implemented in TensorFlow—to detect and classify fake news. Describes preprocessing and feature engineering steps including word2vec dense vectors, feature selection, PCA, and how to build a scalable machine-learning architecture for the task.
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chapters (8)
- 0:00Intro
- 0:38OUTLINE
- 1:06WHAT WHY AND IT'S IMPLICATIONS
- 3:04DATA SET/CORPUS EXPLORATION
- 4:39DEEP LEARNING APPROACHES
- 8:06CONVOLUTIONAL NEURAL NETWORKS IN TEXT CLASSIFICATION
- 13:35NETWORK ARCHITECURE
- 17:07RESULTS SUMMARY
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