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Powerful and flexible environment to develop apps in the cloudĪ powerful, lightweight code editor for cloud development Modernize Cassandra data clusters with a managed instance in the cloudĭeploy applications to the cloud with enterprise-ready, fully managed community MariaDBīuild, manage, and continuously deliver cloud applications-using any platform or language Modernize SQL Server applications with a managed, always-up-to-date SQL instance in the cloudĪccelerate apps with high-throughput, low-latency data cachingĪzure Managed Instance for Apache Cassandra Support rapid growth and innovate faster with secure, enterprise-grade, and fully managed database servicesīuild apps that scale with managed and intelligent SQL database in the cloudįully managed, intelligent, and scalable PostgreSQL

Seamlessly manage Kubernetes clusters at scaleĪzure Kubernetes Service Edge Essentials is an on-premises Kubernetes implementation of Azure Kubernetes Service (AKS) that automates running containerized applications at scale. Launch containers with hypervisor isolationĭeploy and operate always-on, scalable, distributed appsīuild, store, secure, and replicate container images and artifacts

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Run containerized web apps on Windows and Linux Provision unused compute capacity at deep discounts to run interruptible workloadsīuild and deploy modern apps and microservices using serverless containersĭevelop and manage your containerized applications faster with integrated toolsĭeploy and scale containers on managed Red Hat OpenShift Migrate SQL Server workloads to the cloud at lower total cost of ownership (TCO) Manage and scale up to thousands of Linux and Windows VMsīuild and deploy Spring Boot applications with a fully managed service from Microsoft and VMwareĪ dedicated physical server to host your Azure VMs for Windows and LinuxĬloud-scale job scheduling and compute management Remove data silos and deliver business insights from massive datasetsĪccess cloud compute capacity and scale on demand-and only pay for the resources you use Secure, develop, and operate infrastructure, apps, and Azure services anywhere Jump in and explore a diverse selection of today's quantum hardware, software, and solutions Quickly create powerful cloud apps for web and mobileĮverything you need to build and operate a live game on one platformĮxecute event-driven serverless code functions with an end-to-end development experience Migrate, modernize, and innovate on the modern SQL family of cloud databasesīuild or modernize scalable, high-performance appsĭeploy and scale containers on managed KubernetesĪdd cognitive capabilities to apps with APIs and AI services Provision Windows and Linux VMs in secondsĮnable a secure, remote desktop experience from anywhere

Experience with Python or R is not required but preferred.Explore some of the most popular Azure products.

Basic concepts of Azure Machine Learning.

#AZURE NOTEBOOKS HOW TO#

Anyone interested in learning how to use the Azure Machine Learning SDK.Individuals studying to take the Azure DP-100 exam.Use the Azure Machine Learning SDK to perform machine learning tasks.Create a compute instance to host an Azure Notebook.Explore the benefits of using an Azure Notebook.Upon completion of this lab playground, you will be able to: Y ou will use Azure Notebooks and launch a Jupyter notebook sample from the repository to explore using the Azure Machine Learning SDK to create experiments and train models.

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The playground is a safe and secure sandbox environment for you to explore your own ideas, follow along with Cloud Academy courses, or answer your own questions all without the need to install any software on your local machine. These samples are a great way to explore and learn the SDK capabilities, which enables data scientists to use cloud-hosted services to speed up development. The Azure Machine Learning Notebooks repository contains samples and tutorials using the Azure Machine Learning SDK with Python or R. Data scientists, teachers, and students can dive right into learning without spending time installing software. The tedious task of set up and installing all the tools for a data science environment is automated.

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A full Jupyter notebook environment is hosted in the cloud and provides access to an entire Anaconda environment. Azure Notebooks enables data scientists and machine learning engineers to build and deploy models using Jupyter notebooks from within the Azure ML Workspace.

Azure notebooks