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CodeSignal

Understanding Embeddings and Vector Representations

via CodeSignal

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Overview

This course introduces vector embeddings, why they are useful for search, and how to generate them using different models like OpenAI and Hugging Face.

Syllabus

  • Unit 1: Vector Embeddings with OpenAI in Python
    • Enhance Embedding Function Efficiency
    • Fixing Input Handling in Embeddings
    • Calculating Text Similarity with Embeddings
  • Unit 2: Generating Embeddings with Hugging Face Models in Python
    • Tensor Embeddings for Deep Learning
    • Fix the Embedding Function Call
    • Pooling Embeddings for Insights
  • Unit 3: Comparing Vector Embedding Models in Python
    • Calculate Cosine Similarity from Scratch
    • Enhance OpenAI Embeddings Comparison
    • Comparing Embedding Models Effectively
  • Unit 4: Saving and Using Embeddings Locally in Python
    • Save and Store Embeddings Efficiently
    • Loading and Verifying Embeddings
    • Comparing JSON and Pickle Efficiency

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