Word and Sentence Embedding Models Explained
AI Models understand only numbers. Models like large language models first need text to be converted into numbers before they can process them. Vector Embedding Models are designed to do just that
In this video, we overview how Vector Embedding models for text work. We start by understanding how embedding models work for words. Then we extend our understand for text models with a focus on the Sentence Transformer or Sentence BERT model.
We also demonstrate how to use the sentence transformer model in python.
This series is taught by Dr Anil Variyar, who has a PhD in Aeronautics and Astronautics from Stanford University.
00:00 - 01:30 - What is a Vector Embedding
01:30 - 03:28 - Why Embedding Models
03:28 - 07:04 - Understanding Word Embeddings
07:04 - 09:02 - Vector Distances
09:02 - 12:58 - Applications
12:58 - 14:28 - Introduction to Sentence Embeddings
14:28.- 17:35 - What are Sentence Transformers
17:35 - 25:00 - Practical Implementation with Python
25:00 - 26:35 - Conclusion
#deeplearning #generativeai #artificialintelligence #machinelearning #neuralnetworks