Amazon SageMaker is a fully managed service that enables developers and data scientists to build, train, and deploy machine learning (ML) models quickly. It provides algorithms, notebooks, APIs and scalable infrastructure for building ML models. Some key features of SageMaker include algorithms for common ML tasks, notebooks for developing models, APIs for training and deployment, and scalable infrastructure for training and hosting models. It also integrates with other AWS services like S3, EC2 and VPC.
The document appears to be a presentation on Amazon EMR and related AWS services. It discusses using EMR for big data and analytics workloads, how to set up EMR clusters on AWS, encryption options for data at rest and in transit, and integration of EMR with other AWS services like S3 and Spark. The presentation contains many bullet points and diagrams but provides little surrounding context or narrative.
This document provides an overview and agenda for an AWS webinar on AWS Glue. It introduces AWS Glue as a fully managed and serverless ETL service that can manage metadata for various data sources. The webinar will cover the background of AWS Glue, its key features including being serverless and enabling secure development in notebooks, use cases, pricing, and a conclusion. It also provides details on the components and functions of AWS Glue like the data catalog, orchestration, and serverless engines.
This document provides an overview of Elastic Load Balancing (ELB) on AWS. It discusses the different types of ELBs (Application Load Balancer, Network Load Balancer, Classic Load Balancer), their key features and how they can be used to build scalable and highly available systems by distributing traffic across multiple Availability Zones and targets like EC2 instances or ECS containers. It also covers topics like listener configurations, routing, health checks, access logs and integration with other AWS services.
This document discusses Amazon Neptune, a fully managed graph database service. It provides an overview of graphs and graph databases, introduces Amazon Neptune's key features like high performance, availability and security. Gremlin and property graph models are explained. The webinar will cover what graphs are, graph databases, an introduction to Amazon Neptune, getting started with Neptune and a conclusion.
恬って(欧靴藤)僥ふ?インタ`ネットのしくみ サイハ?`エ`シ?ェントのgY喘ASのB初 / Introduce experimental AS in ...whywaita
?
サイバ`エ`ジェントの芙坪エンジニアカンファレンス CA BASE CAMP 2021でk燕したY創です
壅アップロ`ド井: https://speakerdeck.com/whywaita/as-introduce-experimental-as-in-cyberagent-internet-seminer
This document discusses Amazon Neptune, a fully managed graph database service. It provides an overview of graphs and graph databases, introduces Amazon Neptune's key features like high performance, availability and security. Gremlin and property graph models are explained. The webinar will cover what graphs are, graph databases, an introduction to Amazon Neptune, getting started with Neptune and a conclusion.
恬って(欧靴藤)僥ふ?インタ`ネットのしくみ サイハ?`エ`シ?ェントのgY喘ASのB初 / Introduce experimental AS in ...whywaita
?
サイバ`エ`ジェントの芙坪エンジニアカンファレンス CA BASE CAMP 2021でk燕したY創です
壅アップロ`ド井: https://speakerdeck.com/whywaita/as-introduce-experimental-as-in-cyberagent-internet-seminer
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60. GP 2.1 M圭を_羨する
GP 2.2 プロセスを鮫する
GP 2.3 Y坿を戻工する
GP 2.4 販を護り輝てる
GP 2.5 繁Tをトレ`ニングする
GP 2.6 恬I撹惚麗を崙囮する
GP 2.7 岷俊の旋墾vS宀を蒙協しv嚥させる
GP 2.8 プロセスをOし崙囮する
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GP 2.10 貧了レベルの砿尖咾塙欧没rをレビュ`する
GP 3.1 協xされたプロセスを_羨する
GP 3.2 プロセスvBのUY秤鵑鮗める
60
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