[Silicon Valley Artisan Instructor Lecture 4th] Fake News Detection with Big Data——Based on the T-distributed Stochastic Neighbor Embedding Algorithm

[Silicon Valley Artisan Instructor Lecture 4th] Fake News Detection with Big Data——Based on the T-distributed Stochastic Neighbor Embedding Algorithm was successfully held online at PST:6:00PM ,Dec 10th,2020

In this era of unprecedented prosperity of fake news, misleading information is flooded in the media we visit daily, and how to identify reliable news sources is facing severe challenges. When manual identification is difficult to work, we need to collect computing resources and build models to detect fake news.

In terms of algorithms, the T-distributed Stochastic Neighbor Embedding (t-SNE, t-distributed Stochastic Neighbor Embedding) is a very popular method for dimensionality reduction of high-dimensional data and has been widely used in the field of machine learning. In this lecture, Ranyang, a Silicon Valley Artisan Instructor, will also demonstrate its characteristics, advantages, and usage.

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