Back to Module 1.7: EmbeddingsComing Soon
AI Lesson & Submodule
Chunking for Embeddings
Analyze fixed-size, recursive, and semantic document chunking.
Why This Matters
Poor chunking cuts sentences in half, causing vector databases to fail to retrieve relevant passages.
What You Will Learn
- •Implement character chunking
- •Setup recursive chunkers
- •Evaluate semantic splits
Concepts Covered
Character overlapsRecursive token chunkingSemantic split boundaries
Mapped Foundation Project: Resume / JD Matcher
Semantic matching workspace that parses resumes, converts paragraphs into vector embeddings, and measures job description fits.
Architecture Preview
Pipeline mapping files uploads to text, calling embed endpoints, and plotting relative match score vectors.
PDF Resume InputJD Text InputEmbeddings API
Tech Stack Planned
ReactTypeScriptChart.js
GitHub: Coming SoonLive Demo: Coming Soon
Coming SoonTechnical Interview Value
- ?Explain the trade-offs of fixed-size character chunking vs recursive paragraph chunking in document parsing