Himanshu Dhiman
成为会员时间:2023
白银联赛
4060 积分
成为会员时间:2023
这是一节入门级微学习课程,探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能,还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。
This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
在本课程中,您将获得在 Looker 中应用高级 LookML 概念 的实践经验。您将学习如何使用 Liquid 自定义和创建动态 维度和测量、创建动态 SQL 派生表和自定义原生 派生表,并运用扩展功能来模块化你的 LookML 代码
在本课程中,您将通过实操练习掌握 Looker 中的 LookML。您将学习如何编写 LookML 代码来创建新的维度和度量、创建派生表并将其与“探索”联接、为“探索”设置过滤条件, 以及在 LookML 中定义缓存政策。