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OpenAI API: Embeddings

OpenAI API: Embeddings

28mIntermediate2024-01-25

Authors

Kesha Williams

Kesha Williams

Software Engineering Manager, Speaker, Tech Blogger

Course details

Embeddings enable a wide range of natural language processing (NLP) and machine learning capabilities by transforming text into a format that machines can understand. In this course, join instructor Kesha Williams as she covers the basics of embeddings and their practical applications in text classification, clustering, semantic search, and more, with hands-on coding examples along the way.

Learn how to use and manage embeddings through the embeddings API, addressing cost and storage aspects as you go. Kesha provides an overview of the complexities and ethics of embeddings, highlighting common inherent biases and the future of AI technologies. By the end of this course, you’ll have a richer understanding of the theoretical knowledge and practical skills required to effectively apply embeddings in a wide range of use case scenarios.

Skills covered

OpenAI APIAPIsOpenAIGenerative AIArtificial Intelligence (AI)Software DevelopmentOne-Off

Concepts

0. Introduction

  • 01 - Introduction to embeddings

1. Understanding Embeddings

  • 02 - Explore embeddings
  • 03 - Leverage cosine similarity

2. Obtaining Embeddings via the Embeddings API

  • 04 - Explore the Embeddings API
  • 05 - Estimate embeddings pricing
  • 06 - Generate embeddings for a single word

3. Using Embeddings in the Real World

  • 07 - Cluster similar words
  • 08 - Generate embeddings for sentences

Conclusion

  • 09 - Your embeddings journey

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