Text and Code Embeddings: Applications and Advancements - Lecture
Offered By: Open Data Science via YouTube
Course Description
Overview
Explore the transformative power of embeddings in text and code through this insightful 31-minute talk by Dr. Arvind Neelakantan, PhD. Delve into how numerical representations of concepts are revolutionizing natural language processing and code-related tasks, including semantic search, clustering, topic modeling, and classification. Learn about OpenAI's embeddings outperforming top models in key benchmarks, with a 20% relative improvement in code search. Gain valuable insights for enhancing data science and NLP skills, covering topics such as the history of embeddings, contrastive training, experimental results, retrieval techniques, and future directions in the field. Perfect for professionals and enthusiasts in machine learning, deep learning, artificial intelligence, and data science looking to stay at the forefront of embedding technology advancements.
Syllabus
- Embeddings
- Use Cases
- Brief history of embeddings in the last decade
- Contrastive Training
- Recipe
- Experiments
- Retrieval
- Future Directions
Taught by
Open Data Science
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent