RNNs and Attention
Garrett explains the functionality of RNNs, particularly in sentiment classification and text summarization. He highlights the encoder-decoder architecture and the evolution of models through the introduction of attention, which enhances the decoder's ability to focus on relevant parts of the input sequence for generating coherent summaries. This discussion sheds light on the complexities of language generative modeling and the improvements that attention mechanisms provide.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Natural Language Processing at StockTwits with Garrett Hoffman - TWiML Talk #194
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