4 Integrations with IBM Distributed AI APIs

View a list of IBM Distributed AI APIs integrations and software that integrates with IBM Distributed AI APIs below. Compare the best IBM Distributed AI APIs integrations as well as features, ratings, user reviews, and pricing of software that integrates with IBM Distributed AI APIs. Here are the current IBM Distributed AI APIs integrations in 2024:

  • 1
    TensorFlow

    TensorFlow

    TensorFlow

    An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.
    Starting Price: Free
  • 2
    Kubernetes

    Kubernetes

    Kubernetes

    Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.
    Starting Price: Free
  • 3
    Red Hat OpenShift
    The Kubernetes platform for big ideas. Empower developers to innovate and ship faster with the leading hybrid cloud, enterprise container platform. Red Hat OpenShift offers automated installation, upgrades, and lifecycle management throughout the container stack—the operating system, Kubernetes and cluster services, and applications—on any cloud. Red Hat OpenShift helps teams build with speed, agility, confidence, and choice. Code in production mode anywhere you choose to build. Get back to doing work that matters. Red Hat OpenShift is focused on security at every level of the container stack and throughout the application lifecycle. It includes long-term, enterprise support from one of the leading Kubernetes contributors and open source software companies. Support the most demanding workloads including AI/ML, Java, data analytics, databases, and more. Automate deployment and life-cycle management with our vast ecosystem of technology partners.
    Starting Price: $50.00/month
  • 4
    PyTorch

    PyTorch

    PyTorch

    Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.
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