September 2022
Intermediate to advanced
549 pages
11h 27m
Chinese
Overview
通过阅读这本实用手册，人工智能（AI）和机器学习（ML）从业者将会学习如何在Amazon网络服务（AWS）上成功构建并部署数据科学项目。Amazon AI和ML服务栈将数据科学、数据工程和应用开发统一在一起，来帮助你提升技能。这本手册向你展示如何在云上搭建和运行流水线，并将运行结果在几分钟内（而不是几天）集成到应用中。此外，本书作者还在全书各个章节点明了降低开销并提升性能的方法。
- 将Amazon AI和ML服务栈应用到真实世界的应用场景，如自然语言处理、计算机视觉、欺诈检测、对话式设备等。
- 使用Amazon SageMaker Autopilot，通过自动化机器学习（AutoML）实现特定应用场景的子集。
- 深入理解一个基于BERT的自然语言处理场景的模型开发的完整生命周期，包括数据接入、数据分析以及更多。
- 将所有组件包装成一个可重复的机器学习运维流水线。
- 通过Amazon Kinesis和Amazon Managed Streaming for Apache Kafka（MSK），在实时数据流中探索实时机器学习、异常检测和流分析。
- 了解数据科学项目和工作流中的最佳安全实践，包括在数据接入和分析、模型训练和部署过程中应用AWS Identity and Access Management（IAM）、鉴权、授权。
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