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    Red Hat Ansible Automation Platform on Microsoft Azure

    Red Hat Ansible Automation Platform on Azure allows you to quickly deploy, automate, and manage resources securely and at scale.

    Deploy Red Hat Ansible Automation Platform on Microsoft Azure for a strategic automation solution that allows you to orchestrate, govern and operationalize your Azure environment.
  • Multi-Site Network and Cloud Connectivity for Businesses Icon
    Multi-Site Network and Cloud Connectivity for Businesses

    Internet connectivity without complexity

    As your users rely more and more on Cloud and Internet-based technologies, reliable internet connectivity becomes more and more important to your business. With Bigleaf’s proven SD-WAN architecture, groundbreaking AI, and DDoS attack mitigation, you can finally deliver the reliable internet connectivity your business needs without the limitations of traditional networking platforms. Bigleaf’s Cloud Access Network and plug-and-play router allow for limitless control to and from anywhere your traffic needs to go. Bigleaf’s self-driving AI automatically identifies and adapts to any changing circuit conditions and traffic needs—addressing issues before they impact your users. Bigleaf puts you in the driver’s seat of every complaint and support call with full-path traffic and network performance data, delivered as actionable insights, reports, and alerts.
  • 1
    FFCV

    FFCV

    Fast Forward Computer Vision (and other ML workloads!)

    ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations.
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  • 2
    GluonTS

    GluonTS

    Probabilistic time series modeling in Python

    ..., by removing the last three years (36 months) from the train data. Thus, we will train a model on just the first nine years of data. Python has the notion of extras – dependencies that can be optionally installed to unlock certain features of a package. We make extensive use of optional dependencies in GluonTS to keep the amount of required dependencies minimal. To still allow users to opt-in to certain features, we expose many extra dependencies.
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