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Text Representation Techniques for RAG Systems with Java

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Overview

Learn how to represent text effectively for Retrieval-Augmented Generation (RAG). Explore the importance of text representation, compare Bag-of-Words and embeddings, visualize embeddings with t-SNE, and assess their performance in document retrieval and semantic search.

Syllabus

Unit 1: Text Representation with Java: Bag-of-Words model

Text Preprocessing in Java
Creating a Vocabulary Dictionary in Java
Transform Text into Numeric Vectors
Bag-of-Words Vectorization in Java

Unit 2: Generating and Comparing Sentence Embeddings with Java

Generating and Exploring Sentence Embeddings in Java
Cosine Similarity of Sentence Embeddings in Java
Finding the Most Similar Sentence Pair Using Cosine Similarity
Adding and Comparing Sentences with Cosine Similarity in Java
Sentence Similarity Ranking in Java

Unit 3: Visualizing Sentence Embeddings with t-SNE in Java

Visualizing Sentence Embeddings with t-SNE in Java
Troubleshooting and Refining t-SNE Embeddings in Java
Adding a New Category to Sentence Embeddings Visualization in Java

Unit 4: Comparing Bag-of-Words and Embedding-Based Search Techniques in Java

Bag-of-Words Vectorization in Java
Incorporating Bigrams into Bag-of-Words Vectorization
BOW Search Implementation in Java
Implementing Semantic Search with Cosine Similarity in Java

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