Showing 6 open source projects for "environment variables"

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  • 1
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. 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...
    Downloads: 4 This Week
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  • 2
    PML

    PML

    The easiest way to use deep metric learning in your application

    This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you...
    Downloads: 1 This Week
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  • 3
    FlubuCore

    FlubuCore

    A cross platform build and deployment automation system

    "FlubuCore - Fluent Builder Core" is a cross-platform build and deployment automation system. You can define your build and deployment scripts in C# using an intuitive fluent interface. This gives you code completion, IntelliSense, debugging, FlubuCore custom analyzers, and native access to the whole .NET ecosystem inside of your scripts. FlubuCore offers a .net (core) console application that uses power of roslyn to compile and execute scripts. Intuitive and easy to learn. C#, fluent...
    Downloads: 0 This Week
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  • 4
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make...
    Downloads: 0 This Week
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  • 5
    U-Net Fusion RFI

    U-Net Fusion RFI

    U-Net for RFI Detection based on @jakeret's implementation

    ...You can find this code at https://gitlab.com/aroffringa/aoflagger. This project will use the aoflagger program within the code, so you may need to ensure that any environment variables are set for aoflagger before use. cite: https://sourceforge.net/p/u-net-fusion-rfi/wiki/cite/
    Downloads: 0 This Week
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  • 6
    GUAJE FUZZY

    GUAJE FUZZY

    Free software for generating understandable and accurate fuzzy systems

    ...GUAJE lets the user define expert variables and rules, but also provide supervised and fully automatic learning capabilities. Both types of knowledge, expert and induced, are integrated under the expert supervision, ensuring interpretability, simplicity and consistency of the knowledge base along the whole process. Notice that, GUAJE is is an upgraded version of the free software called KBCT (Knowledge Base Configuration Tool).
    Downloads: 2 This Week
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