Editorial course preview
What the public course preview actually shows
These 4 complementary views highlight concrete, legible examples from the course presentation.
This diagram illustrates the Retrieval Augmented Generation workflow, showing how text documents are processed into embeddings, searched for nearest neighbors, and fed into an LLM to generate a response.
This screenshot shows a VS Code environment where Python code is used to add movie documents to a ChromaDB vector database in batches and query titles based on descriptions.
This screenshot displays the development environment with Python code for a RAG chatbot on the left and the live Streamlit interface on the right.
This screenshot shows a Jupyter notebook evaluating a sentiment analysis model, featuring a confusion matrix heatmap and an accuracy score calculation.
