camberbridge

aws-ml-jp

SageMakerで機械学習モデルを構築、学習、デプロイする方法が学べるNotebookと教材集

sagemaker-jumpstart-generative-ai-examples

Unlocking Creativity: Generative AI with SageMaker Jumpstart

VideoConvert

alphafold-protein-structure-prediction-with-frontend-app

aws-ml-enablement-workshop

組織横断的にチームを組成し、機械学習による成長サイクルを実現する計画を立てるワークショップ

guidance-for-media2cloud-on-aws

Guidance for Media2Cloud on AWS solution (formerly known as AWS Media2Cloud Solution) is designed to demonstrate a serverless ingest framework that can quickly setup a baseline ingest workflow for placing video assets and associated metadata under management control of an AWS customer.

aws-media-services-simple-live-workflow

Workshop that covers AWS Elemental MediaLive, MediaPackage, and MediaTailor services

web_3_development_training

ColabFold

Making Protein folding accessible to all!

aws-batch-architecture-for-alphafold

aws-media-services-simple-vod-workflow

Lab that covers video conversion workflow for Video On Demand using AWS MediaConvert.

mlnote-note

機械学習帳を学ぶノート

amazon-elasticsearch-intro-workshop

Amazon Elasticsearch Service workshop for beginners.

media-services-application-mapper

Media Services Application Mapper is a browser-based tool that allows operators to visualize the structure and logical connections among AWS Media Services and supporting services in the cloud. The tool can be used as a top-down resource monitoring tool when integrated with CloudWatch.

ecs-fargate-drain-function

aws-fargate-fast-autoscaler

AWS Fargate Fast Autosaler - A Serverless Implementation that Triggers your Fargate Autoscaling in Seconds

libarib25

Linux用ARIB STD-B25ライブラリ（各録画ツールにarib25ソースを添付しなくとも、Makefile内で-larib25でコンパイルできる）

virtual-waiting-room-on-aws

Virtual Waiting Room on AWS solution helps absorb and control incoming user requests to your website during an unusually large burst of traffic, usually due to a large-scale event.

sagemaker-hf-media-entertainment-summarizer

sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker

workload-discovery-on-aws

Workload Discovery on AWS is a solution to visualize AWS Cloud workloads. With it you can build, customize, and share architecture diagrams of your workloads based on live data from AWS. The solution maintains an inventory of the AWS resources across your accounts and regions, mapping their relationships and displaying them in the user interface.

media-insights-on-aws

A serverless framework to accelerate the development of applications that discover next-generation insights in your video, audio, text, and image resources by utilizing AWS Machine Learning and Media services.

hls.js

HLS.js is a JavaScript library that plays HLS in browsers with support for MSE.

amazon-ivs-auto-captions-web-demo

Use Amazon IVS in conjunction with Amazon Transcribe to deliver real-time captions for live streams.

live-streaming-with-automated-multi-language-subtitling

Live Streaming with Automated Multi-Language Subtitling is a project to automatically generates multi-language subtitles for live streaming web video content. Adding subtitles to your live video content can help improve reach and access, exposing your content to a much larger audience.

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

amazon-textract-response-parser

Parse JSON response of Amazon Textract

amazon-textract-code-samples

Amazon Textract Code Samples

aws-media-replay-engine

Media Replay Engine (MRE) is a framework to build automated video clipping and replay (highlight) generation pipelines for live and video-on-demand content.

studio-lab-examples

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!