What Is React Native? Beginner’s Guide + FAQ
August 9, 2024
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了解预测式 AI 和生成式 AI 中模型评估的细微差别,认识到其在 MLOps 生命周期中发挥的重要作用。
针对不同的生成式 AI 任务确定和应用适当的评估指标。
利用 Vertex AI 的各种评估服务(包括基于计算和基于模型的方法)高效评估生成式 AI。
遵循大语言模型评估的最佳实践,以确保在生产环境中稳健可靠地部署模型。
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"本课程能让机器学习从业者掌握评估生成式和预测式 AI 模型的基本工具、方法和最佳实践。要确保机器学习系统在实际运用中提供可靠、准确、高效的结果,做好模型评估至关重要。
学员将深入了解各项评估指标、方法及如何在不同模型类型和任务中适当应用这些指标和方法。课程将着重介绍生成式 AI 模型带来的独特挑战,并提供有效解决这些挑战的策略。通过利用 Google Cloud 的 Vertex AI Platform,学员可学习如何在模型选择、优化和持续监控工作中实施卓有成效的评估流程。"
本单元介绍了课程目标并概述了课程结构。
本单元介绍了模型评估面临的挑战,以及 Vertex AI 提供的解决方案。
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本单元介绍了评估生成式 AI 任务面临的挑战以及克服这些挑战的最佳实践。本单元还涵盖了 Vertex AI 提供的各类模型评估服务,并介绍了 Vertex AI 自动指标、自动并排评估和安全偏见评估服务。
7 videos1 reading1 assignment
本单元回顾了一些重要的概念、工具、方法和产品,对整个课程进行总结。
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