video1.0<iframe src="https://www.loom.com/embed/02cf9312154e411aa796c1d6b3f650b5" frameborder="0" width="1664" height="1248" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12481664Loomhttps://www.loom.com12481664https://cdn.loom.com/sessions/thumbnails/02cf9312154e411aa796c1d6b3f650b5-1b9307dca0e45f9d.gif3755.7231In this video, I delve into the concept of embeddings in Natural Language Processing, explaining how they help us understand the relationship between queries and documents. I discuss the trade-off between accuracy and computational cost, emphasizing the importance of context in information retrieval. I demonstrate the process of converting figures into paragraphs and the significance of cosine similarity in a high-dimensional vector space. No specific action is requested from viewers, but the video aims to enhance understanding of NLP techniques.