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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数据科学的应用场景
｜
73
如下是一个简单示例：
USING FUNCTION predict_sentiment(review_body VARCHAR(65535))
RETURNS VARCHAR(10) TYPE
SAGEMAKER_INVOKE_ENDPOINT WITH (sagemaker_endpoint = '<ENDPOINT_NAME>')
SELECT predict_sentiment(review_body) AS sentiment
FROM "dsoaws"."amazon_reviews_tsv"
WHERE predict_sentiment(review_body)="POSITIVE";
2.15.5
用
Amazon Neptune
在图数据上运行预测
Amazon Neptune
是一个完全托管的图数据库，其允许我们在高度联系的数据集上构
建并运行应用。
Neptune ML
实现了图神经网络（
graph neural networks
，
GNN
）来
用图数据进行预测。与像
XGBoost
这样的算法只用于传统的表式数据集不同，
GNN
特意为图的复杂性以及潜在的上百万的关系而设计。
Neptune ML
使用开源的
Deep
Graph
库和
Amazon SageMaker
来为图数据自动选择、训练并部署最优模型。
2.16
培养下一代人工智能和机器学习开发者
Amazon
和
AWS
提供许多项目和服务来帮助培养下一代
AI/ML
开发者。过去用
来培训
Amazon ...
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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.