Master Vertex AI - 将 LLM 与文本嵌入 API 结合使用
- 1 - Introduction
- 1 - Introduction and About the Course Prerequisites
- 2 - Course Structure
- 3 - Development Environment Setup Google Cloud Platform Setup
- 4 - Development Environment Setup and API Costs Overview
- 5 - Google Cloud Setup
- 6 - Handson Testing the Vertex AI Generated a Sentence Embedding
- 4 - Vertex AI Text Embedding API and Embeddings Crash Course Deep Dive
- 7 - Introduction to Vertex AI and Capabilities Overview
- 8 - OPTIONAL Embeddings Crash Course
- 9 - How are Embeddings Used in GenAI and LLMs and Use Cases
- 10 - The Embeddings API Text vs Multimodal Embeddings Overview
- 11 - Task Types and Benefits
- 12 - Multimodal Embeddings Diagram
- 13 - Handson Embeddings Length Dimension
- 14 - Handson Run Cosine Similarity Search on Different Sentences
- 15 - Handson Visualize Embeddings
- 16 - Summary
- 5 - Text Generation with Vertex AI Text Embedding API
- 17 - TextGenerationModel Generating Text Using bison Model
- 18 - Handson Text Generation Classification Use Case
- 19 - Handson Extract Information into Tables and JSON Formats
- 20 - Handson Controlling Temperature for the Model
- 21 - Handson TopK and TopP
- 22 - Handson Transcript Summarization and Extraction
- 6 - Handson Application and Realworld Use Cases of Embeddings
- 23 - Cluster Visualization of StackOverflow Question and Answers in 2D
- 24 - Build Your RAG System with the StackOverflow Data
- 25 - Scale with the Approximate Nearest Neighbor Search HNSW vs Cosine Similarity
- 7 - Next Steps
- 26 - Course Summary and Next Steps