Some thought about Embeddings in Natural Language Processing 

In this video we will experiment with embedding models, showing how we can use a trained model to transform a piece of text in a vector that capture semantic of the text. We will show some visualisations techniques to create a 2D representation of a N-Dimensional vector space.
Python notebook can be found here github.com/alkampfergit/ai-pl...
▬ Contents of this video ▬▬▬▬▬▬▬▬▬▬
00:00 - Introduction to natural language processing and embeddings
00:34 - Using embeddings for sentence context analysis
02:07 - Visualizing vector spaces and their limitations
04:26 - Example sentences to demonstrate vector calculations
05:21 - Concepts of sentence transformation into vectors
09:03 - Using OpenAI for embedding creation
12:44 - Exploration of large vector limits and dimension reduction
14:32 - Performance quality and dimension reduction trade-offs with OpenAI model
17:52 - Video Conclusion

Наука