{"id":31639,"date":"2023-02-15T06:00:00","date_gmt":"2023-02-15T14:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=31639"},"modified":"2023-02-16T09:31:20","modified_gmt":"2023-02-16T17:31:20","slug":"video-highlights-attention-is-all-you-need-paper-explained","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/02\/15\/video-highlights-attention-is-all-you-need-paper-explained\/","title":{"rendered":"Video Highlights: Attention Is All You Need – Paper Explained"},"content":{"rendered":"\n

In this video presentation, Mohammad Namvarpour presents a comprehensive study on Ashish Vaswani and his coauthors’ renowned paper, \u201cAttention Is All You Need<\/a>.\u201d This paper is a major turning point in deep learning research. The transformer architecture, which was introduced in this paper, is now used in a variety of state-of-the-art models in natural language processing and beyond. Transformers are the basis of the large language models (LLMs) we’re seeing today. <\/p>\n\n\n\n

If you wish to get up to speed with transformers, here is an incredible learning resource complete with tutorials, videos, course notes, links to seminal papers, and much more. Visit the GitHub repo HERE<\/a>. <\/p>\n\n\n\n

\n