|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/vespa-ai-search-engine-and-vector-database-with-python/
课程评论：没有评论
**课程名称：** Vespa AI 搜索引擎与向量数据库（Python） **课程概述：** 本课程是一门关于使用 Vespa AI 和 Python 构建高级搜索引擎及向量数据库的综合性指南。课程面向数据科学家、软件开发者、AI 爱好者以及任何对现代搜索技术感兴趣的学习者。 **主要学习内容：** * **Vespa AI 基础：** 深入理解 Vespa AI 的架构、核心组件及其工作原理。 * **向量数据库开发与部署：** 学习如何构建、部署和管理高性能的向量数据库。 * **Python 集成：** 利用 Python 将 Vespa AI 应用于实时数据处理、排序和检索。 * **可扩展搜索引擎构建：** 掌握创建可扩展、高吞吐量搜索应用的方法。 * **机器学习增强搜索：** 学习如何运用机器学习模型优化搜索结果的准确性和相关性。 * **高级搜索技术：** 探索语义搜索、近似最近邻搜索（ANN）以及混合搜索方法。 * **实战项目：** 通过实际项目学习在 Vespa Cloud 上部署应用，使用自定义排序函数优化搜索性能，并实现过滤器和跨命中归一化以提高搜索精度。 **学习目标：** 完成课程后，学员将能够创建和部署强大的、可扩展的搜索应用程序和向量数据库。 **先修要求：** * 具备 Python 基础知识。 * 熟悉 Google Colab。 **课程亮点：** * 提供源代码，便于实践。 * 课程内容全面，涵盖从基础到高级的各类主题。 * 注重实践操作，帮助学习者积累宝贵的实战经验。 本课程旨在为学习者在搜索技术和 AI 集成领域提供宝贵的见解和实践经验。
This course is a comprehensive guide to building advanced search engines and vector databases using Vespa AI and Python. It is designed for data scientists, software developers, AI enthusiasts, and anyone interested in mastering modern search technologies. Throughout this course, you will learn the fundamentals of Vespa AI, including its architecture and core components, and how to leverage its capabilities to build high-performance search applications.You will gain hands-on experience with Python to integrate Vespa AI for real-time data processing, ranking, and retrieval. The course covers essential topics such as developing and deploying vector databases, creating scalable search engines, and using machine learning models to enhance search results. Additionally, you will explore advanced search techniques like semantic search, approximate nearest neighbor search, and hybrid search methods.The course includes practical projects that guide you through deploying applications on Vespa Cloud, optimizing search performance with custom ranking functions, and implementing filters and cross-hit normalization for better search accuracy. By the end of this course, you will have the skills to create and deploy powerful, scalable search applications and vector databases.Prerequisites include a basic understanding of Python and familiarity with Google Colab. This course provides valuable insights and practical experience to advance your knowledge in search technologies and AI integration.Source code is provided in sections.
