AWS Black Belt Online Seminarの最新コンテンツ: https://aws.amazon.com/jp/aws-jp-introduction/#new
過去に開催されたオンラインセミナーのコンテンツ一覧: https://aws.amazon.com/jp/aws-jp-introduction/aws-jp-webinar-service-cut/
This document provides information about an AWS webinar on AWS Step Functions hosted by Yuta Imamura from Amazon Web Services Japan. The agenda includes an overview of Step Functions, state machines, data input and output, describing states, checking execution status, and additional details. Step Functions allows orchestrating distributed applications and microservices using state machines defined in Amazon States Language (ASL). States can pass data and parameters between each other to synchronize processes.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
20190402 AWS Black Belt Online Seminar Let's Dive Deep into AWS Lambda Part1 ...Amazon Web Services Japan
This document contains a presentation on AWS Lambda by Keisuke Nishitani, a Solutions Architect at Amazon Web Services Japan. The presentation introduces AWS Lambda as a serverless computing platform that allows users to run code without provisioning or managing servers. It discusses how Lambda allows developers to build applications that scale automatically in response to changes in usage. The presentation also provides an overview of Lambda's programming languages, triggers, execution environment, pricing model, and integration with other AWS services.
- The document discusses Amazon Redshift, a cloud data warehouse service from AWS.
- It provides an overview of Redshift's architecture and how it has evolved over time, including the addition of new instance types.
- It also discusses how Redshift can be used with Amazon S3 as a data lake, through features like Redshift Spectrum, to enable analytics on both data warehouse and lake storage.
The document discusses Amazon Web Services (AWS) Batch and how it can help customers run batch computing workloads on AWS. It notes that AWS Batch automatically provisions the optimal quantity and type of compute resources (e.g., EC2 instances) required to run jobs efficiently. It also allows customers to integrate their own scheduling and application code with AWS Batch through simple API calls or SDKs.
This document discusses the need for a service mesh and introduces AWS App Mesh as a service mesh solution. It explains that as applications become more distributed, microservices-based, and utilize different technologies, a common way to handle communication between services is needed to ensure reliability, security, and observability across the system. A service mesh provides this by managing traffic at the infrastructure level rather than requiring each application to implement its own communication logic.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
20190402 AWS Black Belt Online Seminar Let's Dive Deep into AWS Lambda Part1 ...Amazon Web Services Japan
This document contains a presentation on AWS Lambda by Keisuke Nishitani, a Solutions Architect at Amazon Web Services Japan. The presentation introduces AWS Lambda as a serverless computing platform that allows users to run code without provisioning or managing servers. It discusses how Lambda allows developers to build applications that scale automatically in response to changes in usage. The presentation also provides an overview of Lambda's programming languages, triggers, execution environment, pricing model, and integration with other AWS services.
- The document discusses Amazon Redshift, a cloud data warehouse service from AWS.
- It provides an overview of Redshift's architecture and how it has evolved over time, including the addition of new instance types.
- It also discusses how Redshift can be used with Amazon S3 as a data lake, through features like Redshift Spectrum, to enable analytics on both data warehouse and lake storage.
The document discusses Amazon Web Services (AWS) Batch and how it can help customers run batch computing workloads on AWS. It notes that AWS Batch automatically provisions the optimal quantity and type of compute resources (e.g., EC2 instances) required to run jobs efficiently. It also allows customers to integrate their own scheduling and application code with AWS Batch through simple API calls or SDKs.
This document discusses the need for a service mesh and introduces AWS App Mesh as a service mesh solution. It explains that as applications become more distributed, microservices-based, and utilize different technologies, a common way to handle communication between services is needed to ensure reliability, security, and observability across the system. A service mesh provides this by managing traffic at the infrastructure level rather than requiring each application to implement its own communication logic.
This document lists different CIDR blocks and URLs for downloading files from an S3 bucket. It includes CIDR blocks ranging from /25 to /19 and URLs to download icon.zip and pie.zip files from the mahjong folder in the aws-cloud S3 bucket.
論文紹介:PitcherNet: Powering the Moneyball Evolution in Baseball Video AnalyticsToru Tamaki
Jerrin Bright, Bavesh Balaji, Yuhao Chen, David A Clausi, John S Zelek,"PitcherNet: Powering the Moneyball Evolution in Baseball Video Analytics" CVPR2024W
https://openaccess.thecvf.com/content/CVPR2024W/CVsports/html/Bright_PitcherNet_Powering_the_Moneyball_Evolution_in_Baseball_Video_Analytics_CVPRW_2024_paper.html
論文紹介:"Visual Genome:Connecting Language and VisionUsing Crowdsourced Dense I...Toru Tamaki
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei ,"Visual Genome:Connecting Language and VisionUsing Crowdsourced Dense Image Annotations" IJCV2016
https://link.springer.com/article/10.1007/s11263-016-0981-7
Jingwei Ji, Ranjay Krishna, Li Fei-Fei, Juan Carlos Niebles ,"Action Genome: Actions As Compositions of Spatio-Temporal Scene Graphs" CVPR2020
https://openaccess.thecvf.com/content_CVPR_2020/html/Ji_Action_Genome_Actions_As_Compositions_of_Spatio-Temporal_Scene_Graphs_CVPR_2020_paper.html