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Showing 159 open source projects for "amazon"
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SCIPIO ERP
eCommerce framework for multinational omnichannel installations
...Highly configurable products and prices, custom promotions and region-based offerings – the store can handle it all. Our web store is mobile-friendly and full of features you can rely on. And if you want, you can use our existing POS or Amazon integrations to push your exposure to the max! Integrating third–party applications into Scipio ERP is a breeze and cost–efficient. We believe in “composable commerce”, ie. your right to choose your “best-of-breed” vendors to build a solution that fits you like a glove! Out of the box, the platform integrates into a long list of other services and our addons extend the system even further. -
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GSGui is a graphical wrapper for Ghostscript for converting PDF files to the old PDF format (ver 1.4) for Amazon Kindle 4 ------------->>> Java 8 and Ghostscript must be installed on your system before use
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Amazon Braket Strawberry Fields Plugin
An open source framework for using Amazon Braket devices
An open-source framework for using Amazon Braket devices with the Strawberry Fields photonic device programming library. This plugin provides a BraketEngine class for running photonic quantum circuits created in Strawberry Fields on the Amazon Braket service. The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. -
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Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Amazon Kinesis Video Streams Parser Lib
Easy to work with the output of video streams
Amazon Kinesis Video Streams parser library is for developers to include in their applications that makes it easy to work with the output of video streams such as retrieving frame-level objects, metadata for fragments, and more. The Amazon Kinesis Video Streams Parser Library for Java enables Java developers to parse the streams returned by GetMedia calls to Amazon Kinesis Video. -
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Knet
Koç University deep learning framework
...If you would like to try it on your own computer, please follow the instructions on Installation. If you would like to try working with a GPU and do not have access to one, take a look at Using Amazon AWS or Using Microsoft Azure. If you find a bug, please open a GitHub issue. If you don't have access to a GPU machine, but would like to experiment with one, Amazon Web Services is a possible solution. I have prepared a machine image (AMI) with everything you need to run Knet. Here are step-by-step instructions for launching a GPU instance with a Knet image (the screens may have changed slightly since this writing). -
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Amazon EKS Anywhere Curated Packages
EKS Anywhere Curated Packages is a management system for installation
The EKS Anywhere package controller and the EKS Anywhere Curated Packages (referred to as “features”) are provided as “preview features” subject to the AWS Service Terms, (including Section 2 (Betas and Previews)) of the same. During the EKS Anywhere Curated Packages Public Preview, the AWS Service Terms are extended to provide customers access to these features free of charge. These features will be subject to a service charge and fee structure at the”General Availability“ of the features.... -
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Electron Release Server
A fully featured, self-hosted release server for electron applications
...Awesome release management interface powered by AngularJS. Authenticates with LDAP, easy to modify to another authentication method if needed. Store assets on server disk, or Amazon S3 (with minor modifications). Use pretty much any database for persistence, thanks to Sails & Waterline. Simple but powerful download urls (NOTE: when no assets are uploaded, server returns 404 by default). -
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ECS Deploy
Powerful CLI tool to simplify Amazon ECS deployments, rollbacks, etc.
ecs-deploy simplifies deployments on Amazon ECS by providing a convenience CLI tool for complex actions, which are executed pretty often. Support for complex task definitions (e.g. multiple containers & task role), easily redeploy the current task definition (including docker pull of eventually updated images), deploy new versions/tags or all containers or just a single container in your task definition, scale up or down by adjusting the desired count of running tasks, add or adjust containers environment variables. ... -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. -
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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. ... -
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Open Guide to AWS
Amazon Web Services — a practical guide
og-aws (The Open Guide to Amazon Web Services) is a community-maintained reference that consolidates tips, best practices, and practical knowledge for effectively using AWS. Unlike official AWS documentation, which provides only formal product details, this guide integrates real-world experiences, advice, and caveats gathered from engineers who work with AWS daily. -
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Amazon Braket Ocean Plugin
A Python plugin for using Ocean with Amazon Braket
The Amazon Braket Ocean Plugin is an open-source library in Python that provides a framework that you can use to interact with Ocean tools on top of Amazon Braket. Before you begin working with the Amazon Braket Ocean Plugin, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. -
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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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Amazon Neptune Gremlin .NET SigV4
A custom library for Amazon Neptune that enables AWS Signature Version
This project provides a custom library that extends the Apache TinkerPop Gremlin.NET client to enable AWS IAM Signature Version 4 signing for establishing authenticated connections to Amazon Neptune. For example usage refer to: NeptuneGremlinNETSigV4Example.cs. This example shows how to leverage this library for establishing an authenticated connection to Neptune. The GremlinClient library accepts both a GremlinServer object as well as a webSocketConfiguration object that contains a custom configuration set for establishing the WebSocket connection to Amazon Neptune. ... -
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Mongoose OS
IoT firmware development framework
Mongoose OS, an IoT Firmware Development Framework. Supported microcontrollers, ESP32, ESP8266, CC3220, CC3200, STM32F4, STM32L4, STM32F7. Amazon AWS IoT, Microsoft Azure, Google IoT Core integrated. Code in C or JavaScript. Mongoose OS is integrated and powers many types of devices and appliances globally. Microsoft Azure IoT recommends Mongoose OS for OTA, automatic device management and deploying firmware updates at scale. Built-in flash encryption, crypto chip support, ARM mbedTLS optimized for small memory footprint. ... -
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Space Cloud
Open source Firebase + Heroku to develop, scale and secure apps
...It provides GraphQL and REST APIs which can be consumed directly by your frontend in a secure manner. Flexible queries, transactions, aggregations and cross-database joins. Make live queries to your database. Upload/download files to scalable file stores (e.g., Amazon S3, Google Cloud Storage). Unified APIs for your custom HTTP services. Trigger webhooks or serverless functions on database or file storage events. Dynamic access control that integrates with your auth system (e.g., auth0, firebase-auth). Written in Golang, it follows cloud-native practices and scales horizontally. -
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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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aws-mwaa-local-runner
CLI that replicates an Amazon Managed Workflows for Apache Airflow
...You can setup the local Airflow's boto with the intended execution role to test your DAGs with AWS operators before uploading to your Amazon S3 bucket. -
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constructs-go
Golang bindings for constructs
...Constructs are part of the Construct Programming Model (CPM) and are also used by other tools such as CDK for Terraform (CDKtf), CDK for Kubernetes (CDK8s), and Projen. A construct can represent a single AWS resource, such as an Amazon Simple Storage Service (Amazon S3) bucket, or it can be a higher-level abstraction consisting of multiple AWS related resources. Examples of such components include a worker queue with its associated compute capacity, or a scheduled job with monitoring resources and a dashboard. The AWS CDK includes a collection of constructs called the AWS Construct Library, containing constructs for every AWS service. -
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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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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. ... -
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BotMan
A framework agnostic PHP library to build chat bots
Write your chatbot logic once and connect it to one of the available messaging services, including Amazon Alexa, Facebook Messenger, Slack, Telegram or even your own Website. BotMan is framework agnostic, which means you can use it in your existing codebase, whatever framework you might use. Starting a new chatbot project? BotMan Studio is a Laravel 5.5 boiler project to get you started in no time! BotMan is all about having an expressive, yet powerful syntax that allows you to focus on the business logic, not on framework code. ... -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. -
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RISC-V BOOM
SonicBOOM: The Berkeley Out-of-Order Machine
The riscv-boom project (also called BOOM or SonicBOOM) implements a high-performance, synthesizable out-of-order RISC-V core written in the Chisel hardware construction language. It targets the RV64GC (i.e. 64-bit with general + compressed + floating point) instruction set and supports features such as virtual memory, caches, atomics, and IEEE-754 floating point. The design is parameterizable, meaning users can tune pipeline widths, buffer sizes, functional units, and other...
