Learn how Neo4j can help you make sense of your unstructured data. Enroll in this new free course on GraphAcademy.
There’s a new course on GraphAcademy: Introduction to Vector Indexes and Unstructured Data.
This course teaches you to understand unstructured data using Neo4j and vector indexes.
You will explore unstructured datasets, create embeddings and vector indexes, and use them to search and understand the data.
During hands-on tasks, you will use vector indexes to find similarities between text and images.
You will learn how to process unstructured data, use chunking strategies, and create relationships between the data.
You will build a graph database of the unstructured GraphAcademy course content — using Python, LangChain, and OpenAI to process the data, create embeddings, and import it into Neo4j.
After completing this course, you will have the knowledge and skill to build a graph of your unstructured data and query it using vector indexes.
Enroll in the Introduction to Vector Indexes and Unstructured Data course on Neo4j GraphAcademy.
What is Neo4j GraphAcademy?
At Neo4j GraphAcademy, we offer a wide range of courses completely free of charge, teaching everything from Neo4j Fundamentals to Building a Neo4j-backed Chatbot using Python.
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Introduction to Vector Indexes and Unstructured Data — New GraphAcademy Course was originally published in Neo4j Developer Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.
