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Blend Hybrid Search

本课程是 Vector DB Foundations, Embeddings & Search Algorithms 专项课程的一部分

位教师：LearningMate

包含在中

了解更多

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Implement a hybrid search system, tuning keyword and vector scores to optimize search relevance using the NDCG metric.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Vector DB Foundations, Embeddings & Search Algorithms 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有2个模块

In the world of AI-powered search, relevance is everything. Go beyond the limits of pure keyword or vector search in Blend Hybrid Search, an intermediate course for developers and ML engineers. You will learn to build a state-of-the-art search system by combining the precision of keyword matching (like BM25) with the semantic power of dense vectors. This course provides a complete, hands-on framework for optimizing search performance using open-source tools as our implementation example.

You won't just build a hybrid search function; you will master the art of tuning it. Through a project-driven approach, you will learn to systematically adjust weighting parameters and use the industry-standard NDCG metric to objectively measure and prove the impact of your changes. You will leave with a reusable evaluation script and a data-driven methodology for squeezing the maximum relevance from any search application.

单元详情

In this module, you will learn the fundamental principles behind state‑of‑the‑art search and immediately put them into practice. You will build a complete hybrid search function from scratch by combining BM25 keyword scores with dense vector scores, and you will experiment with the alpha weighting parameter to understand how it affects ranking behavior. This module establishes the foundation for evaluation and tuning, which you will perform in the next module.

涵盖的内容

1个视频1篇阅读材料1个作业1个非评分实验室

A hybrid system is only as good as its tuning. In this module, you will master the iterative, data-driven process of optimization. You will use a systematic evaluation framework to test different weights, analyze the results with NDCG, and identify the optimal blend to maximize search relevance.