Day 7 - Dense Embedding - RAG
📰 Dev.to · Indumathi R
Learn about dense embeddings in RAG and how they use continuous numeric values to represent data
Action Steps
- Explore the concept of dense embeddings and their application in RAG
- Build a simple RAG model using dense embeddings to understand how they work
- Configure a dense embedding layer in a neural network to represent continuous numeric values
- Test the performance of a RAG model using dense embeddings on a sample dataset
- Apply dense embeddings to a real-world problem, such as text classification or information retrieval
Who Needs to Know This
Data scientists and ML engineers working with RAG can benefit from understanding dense embeddings to improve their model's performance
Key Insight
💡 Dense embeddings use continuous numeric values to represent data, allowing for more nuanced and accurate representations
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🤖 Learn about dense embeddings in RAG and how they can improve your model's performance! #RAG #DenseEmbeddings #ML
Full Article
Dense embedding have continuous numeric values. i.e after decimal point values will be present. Chunk...
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