Search Results for "ml-agents toolkit"
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Showing 5 open source projects for "ml-agents toolkit"
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SageMaker Inference Toolkit
Serve machine learning models within a Docker container
... the container is deployed. Containerizing your model and code enables fast and reliable deployment of your model. The SageMaker Inference Toolkit implements a model serving stack and can be easily added to any Docker container, making it deployable to SageMaker. This library's serving stack is built on Multi Model Server, and it can serve your own models or those you trained on SageMaker using machine learning frameworks with native SageMaker support. -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
... and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies. -
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Zarja
Agent-based simulation toolkit
It is an open source scientific library that is focused on multi-agent simulations on graphs. It prepares basic toolkit for agents, models, timers, graphs, nodes and edges. It is also accompanied with tools for data processing. -
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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. The SageMaker Training Toolkit can be easily added to any... -
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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DRINKS Toolkit
DRINKS is a set of smart web-based widgets.
DRINKS Toolkit is a collection of web-based widget, focused in the first release, to realize an online strumentation. It provides a practical and immediate interface to represent your data in the best possible way. Every widget is drawed using HTML5 Canvas API in a Javascript based environment. Drinks was born to allow users to easily realize custom dashboards without any programming knowledge, infact, you can use your instrument on a webpage simply using HTML tags, or using BarMan IDE...
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