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Showing 10 open source projects for "amazon"
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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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amazon-connect-wisdomjs
Gives you the power to build your own Wisdom widget
Amazon Connect Wisdom, a feature of Amazon Connect, delivers agents the information they need, reducing the time spent searching for answers. Today, knowledge articles, wikis, and FAQs are spread across separate repositories. Agents lose a lot of time trying to navigate all those different sources of information, and in the meantime, the customer waits for an answer. -
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AWS SDK for PHP
Repository of the AWS SDK for PHP
The AWS SDK for PHP makes it easy for developers to access Amazon Web Services in their PHP code, and build robust applications and software using services like Amazon S3, Amazon DynamoDB, Amazon Glacier, etc. You can get started in minutes by installing the SDK through Composer or by downloading a single zip or phar file from our latest release. Before you begin, you need to sign up for an AWS account and retrieve your AWS credentials. -
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AWS Copilot CLI
The AWS Copilot CLI is a tool for developers to build, release apps
AWS Copilot is an open-source command-line interface that makes it easy for developers to build, release, and operate production-ready containerized applications on AWS App Runner, Amazon ECS, and AWS Fargate. Run a single command to quickly get started with a containerized application using best practices on AWS from a Dockerfile. Instead of modeling individual resources, Copilot provides common cloud architectures, request-driven web service, load-balanced web service, backend service, worker service, and scheduled job. ... -
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RDM
Cross-platform GUI management tool for Redis
...RDM supports all latest Redis ® features: ACL, Streams, Cluster, Sentinel, ReJSON module, HyperLogLog, etc. Build-in TLS, SSH and TLS-over-SSH tunneling for easy and secure access to any redis-server. RDM works with Amazon ElastiCache, Microsoft Azure Redis Cache, Digital Ocean and other Redis ® clouds. RDM displays JSON, MessagePack, CBOR, PHP, Pickle, numpy.Array, pandas.DataFrame and binary data in human readable form and supports Native Formatters. RDM offers you an easy-to-use GUI to access your Redis ® databases and perform some basic operations. ... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
...In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance. -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
SageMaker TensorFlow Serving Container is an a open source project that builds docker images for running TensorFlow Serving on Amazon SageMaker. Some of the build and tests scripts interact with resources in your AWS account. Be sure to set your default AWS credentials and region using aws configure before using these scripts. Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. The Docker images are built from the Dockerfiles in docker/. ... -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. -
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Wp App Studio
Wp App Studio is a Wordpress based custom plugin development platform.
Wp App Studio (WPAS) is a cost-effective REST API based software as a service (SaaS) platform that creates fully featured WordPress apps(plugins). Saas is a software delivery model commonly used by companies such as Google, Yahoo, Amazon etc. In SaaS delivery model all processing takes place outside of your computer. WPAS as a SaaS application does not require the deployment of a complex processing infrastructure and algorithms to generate code at your computer. It eliminates or drastically reduces the upfront commitment of resources at your end. WPAS also allows us to meet more complex and advanced requirements without being limited to any client computer profile. ... -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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The AWS Toolkit for Eclipse is a plug-in for the Eclipse Java IDE that makes it easier for developers to develop, deploy, and debug Java applications using Amazon Web Services.
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