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  • Paessler: Easy to Use With Enterprise Power. Free Trial Icon
    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

    You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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    Veeam Data Platform v13.1 - Get Your Free Trial

    Secure by design, portable by default. Recover clean, fast, anywhere. Start a free trial.

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  • 1
    fastai

    fastai

    Deep learning library

    fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying...
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  • 2
    Elephas

    Elephas

    Distributed Deep learning with Keras & Spark

    Elephas is an extension of Keras, which allows you to run distributed deep learning models at scale with Spark. Elephas currently supports a number of applications. Elephas brings deep learning with Keras to Spark. Elephas intends to keep the simplicity and high usability of Keras, thereby allowing for fast prototyping of distributed models, which can be run on massive data sets. Elephas implements a class of data-parallel algorithms on top of Keras, using Spark's RDDs and data frames. Keras...
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  • 3
    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...
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