courseraIT и технологии

運用 BigQuery 建立嵌入項目、向量搜尋和 RAG

Курс от Google Cloud

Продвинутый≈ 2.3 чКитайский (Тайвань)

О курсе

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

Навыки, которые вы освоите

Retrieval-Augmented Generation Vector Databases Google Gemini Embeddings Large Language Modeling Google Cloud Platform Generative AI LLM Application

Программа курса

1 модулей · 9 учебных материалов

01運用 BigQuery 建立嵌入項目、向量搜尋和 RAG9 материалов

Create Embeddings, Vector Search, and RAG with BigQuery

使用 RAG 的原因Видео 嵌入項目Видео 向量搜尋Видео RAG 使用示範Видео 摘要Видео

Учитесь у экспертов

Google Cloud Training

Преподаватель курса