September 2022
Intermediate to advanced
549 pages
11h 27m
Chinese
Content preview from 基于AWS的数据科学实践
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2
｜
前言
本书的概要
第
1
章简要介绍了
Amazon AI
和
ML
栈，这是一个极为强大的集合，提供了可供任
何复杂度和规模的数据科学项目使用的各种服务、开源库以及基础设施。
第
2
章描述了如何将
Amazon AI
和
ML
栈应用在真实世界的使用场景来实现推荐、
计算机视觉、欺诈检测、自然语言理解（
NLU
）、对话式设备、认知搜索、客户支持、
工业预测性维护、家庭自动化、物联网（
IoT
）、医疗卫生和量子计算。
第
3
章演示了如何使用
SageMaker Autopilot
通过
AutoML
实现一些上面提到的场景。
第
4
～
9
章深入介绍了一个基于
BERT
的
NLP
使用场景的、完整的模型开发生命
周期，包括数据接入与分析、特征选择和工程、模型训练、微调和部署，这些步
骤通过
Amazon SageMaker
、
Amazon Athena
、
Amazon Redshift
、
Amazon EMR
、
TensorFlow
、
PyTorch
和无服务器化的
Apache Spark
实现。
第
10
章通过
SageMaker Pipelines
、
Kubeflow Pipelines
、
Apache Airflow
、
MLflow
和
TFX
实现
MLOps
，将所有服务组合集成进可重复的流水线。
第
11
章使用
Amazon Kinesis
和
Apache Kafka
，展示了基于实时数据流的实时
ML
、异常检测和流分析。
第
12
章全面展示了数据科学项目和工作流中的最佳安全实践，包括
IAM
、鉴权、授权、
网络隔离、数据静态加密、后量子网络传输加密、治理和可审计性。
在全书每一章 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.