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Vector Search and Embeddings - 简体中文

Google Cloud Training

本课程介绍 Vertex AI Vector Search,并说明如何使用它来通过嵌入大语言模型 (LLM) API 构建搜索应用。本课程包括以下内容:讲解矢量搜索和文本嵌入概念的讲座、关于如何在 Vertex AI 上构建矢量搜索的实际演示,以及一项实操实验。

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What's inside

Syllabus

矢量搜索和嵌入
本课程介绍 Vertex AI Vector Search,并说明如何使用它来通过嵌入大语言模型 (LLM) API 构建搜索应用。本课程包括以下内容:讲解矢量搜索和文本嵌入概念的讲座、关于如何在 Vertex AI 上构建矢量搜索的实际演示,以及一项实操实验。

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
该课程由Google Cloud Training讲授,他们以在云计算领域的工作而闻名。
本课程融合了文本嵌入、矢量搜索和 LLM 技术,适合具有良好机器学习和 NLP 背景的技术人员和开发人员。
本课程提供动手实验,这对于实践和巩固所学知识至关重要。
通过整合 LLM API,该课程展示了如何利用最新的大语言模型的强大功能。

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Vector Search and Embeddings - 简体中文 with these activities:
Revisit the fundamentals
Review the key concepts of vector search and text embedding to prepare for the course.
Browse courses on Vector Search
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  • Read an overview of vector search and text embedding
  • Review the concepts of vector space models and cosine similarity
  • Complete practice exercises on vector search and text embedding
Solve practice problems
Solve practice problems to improve your understanding of vector search and text embedding.
Browse courses on Vector Search
Show steps
  • Find a set of practice problems related to vector search or text embedding
  • Attempt to solve the problems on your own
  • Review the solutions and identify areas for improvement
  • Repeat until you can confidently solve most of the problems
Join a study group
Join a study group to collaborate with other students, discuss the course material, and learn from each other.
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  • Find a study group or create your own
  • Meet regularly to discuss the course material
  • Share resources and insights with each other
  • Support and motivate each other through the learning journey
Four other activities
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Follow a tutorial on Vertex AI Vector Search
Follow a step-by-step tutorial to set up and use Vertex AI Vector Search for your application.
Show steps
  • Find a tutorial on Vertex AI Vector Search
  • Follow the tutorial to set up Vertex AI Vector Search
  • Experiment with different parameters and options
  • Deploy a vector search application using Vertex AI Vector Search
Contribute to an open-source project
Contribute to an open-source project to gain experience with real-world applications of vector search and text embedding.
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  • Find an open-source project related to vector search or text embedding
  • Review the project documentation and codebase
  • Identify an area where you can contribute
  • Submit a pull request with your contribution
Volunteer in a related field
Volunteer your skills to a non-profit or open-source project related to natural language processing or machine learning.
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  • Find a volunteer opportunity in a related field
  • Contribute your skills and knowledge to the project
  • Learn from experienced professionals
  • Gain practical experience and build your resume
Write a blog post or article
Create a blog post or article to share your knowledge and insights on vector search and text embedding.
Browse courses on Vector Search
Show steps
  • Choose a topic related to vector search or text embedding
  • Research and gather information on the topic
  • Organize your thoughts and ideas into an outline
  • Write your blog post or article
  • Share your blog post or article with others

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