Text Embeddings, Classification, and Semantic Search with Python Code

Explore text embeddings and their practical applications in a 25-minute video tutorial. Learn how to leverage text embeddings for two high-value use cases: text classification and semantic search. Dive into the problem of non-computable text, understand the concept of text embeddings, and discover their importance in natural language processing. Follow along with Python code examples to implement text classification and semantic search techniques. Gain insights into the broader applications of these methods in AI and machine learning. Access additional resources, including a GitHub repository and related articles, to further enhance your understanding of text embeddings and their real-world applications.

Intro -
Problem: Text isn't computable -
Text Embeddings -
Why should I care? -
Use Case 1: Text Classification -
Use Case 2: Semantic Search -
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