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Rasa Algorithm Whiteboard - Spelling Correction
Rasa Algorithm Whiteboard - Translation Issues
Rasa Algorithm Whiteboard - Diet Architecture 1: How it Works
Rasa Algorithm Whiteboard - FlashText Entity Extraction
Rasa Algorithm Whiteboard - Toxic Language Detection
Rasa Algorithm Whiteboard - Understanding Word Embeddings 3: GloVe
Rasa Algorithm Whiteboard - Language Detection
Rasa Algorithm Whiteboard - Universal Sentence Encoder
Rasa Algorithm Whiteboard - Understanding Word Embeddings 2: CBOW and Skip Gram
Rasa Algorithm Whiteboard - Understanding Word Embeddings 1: Just Letters
Rasa Algorithm Whiteboard - Transformers & Attention 1: Self Attention
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Last Updated: September 27, 2026
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Summary
In this video, we will explore pre-trained spaCy models and use them to This is the fourth and final video on attention mechanisms. In the previous video we introduced multiheaded keys, queries and ... This is the second video on attention mechanisms. In the previous video we introduced self attention and in this video we're going ... Spelling Correction is hard, especially when you've only gotten a small amount of data to work with. It's no surprise that virtual ... Text translation is hard, especially when you've only gotten a small amount of data to work with. But still ... we may be interested in ... This video explains the separate parts of the DIET architecture and how they are combined into an architecture that is useful in a ... What might an assistant do if it sees a text from a language that it isn't trained on? It might make assumptions because it's unlike ... The Universal Sentence Encoder is an embedding for sentences as opposed to words. There are a few interesting tricks that are ... There are many ways to go from words to vectors (word2vec) and in this video we discuss two approaches; continous bag of ... We're making a few videos that highlight word embeddings. Before training word embeddings we figured it might help the intuition ... This is the first video on attention mechanisms. We'll start with self attention and end with transformers. We're going at it step by ...
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