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Azure Virtual Machine for Machine Learning

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Prerequisites: About Microsoft Azure, Cloud Based Services Some of the Machine Learning and Deep Learning algorithms may require high computation power which may not be supported by your local machine or laptop. In that case, creating a Virtual Machine on a cloud platform can provide you the expected computation power. We can have a system with high RAM, high storage capacity, latest graphics that can speed up the training phase and we can experiment with our model in lesser time. In this article, we will learn to create a Virtual Machine on Microsoft Azure. Microsoft Azure has a free trial offer for the new users. To create a new Microsoft Azure Account for free, visit this link. Step #1: Open your Microsoft Azure Account: Sign in to your Microsoft Azure Account. After you have, open your Azure portal. 

Azure Virtual Machine (VM) is a service provided by Microsoft Azure that allows users to create, configure, and manage virtual machines in the cloud. Azure VMs can be used for a wide range of purposes, including machine learning. Some of the benefits of using Azure VMs for machine learning include:

Scalability: Azure VMs can be easily scaled up or down to meet the demands of machine learning workloads, which allows users to easily handle large amounts of data and processing power.

Flexibility: Azure VMs can be configured with a wide range of operating systems and software, which allows users to choose the tools and frameworks that best suit their machine learning needs.

Cost-effectiveness: Azure VMs offer a pay-as-you-go pricing model, which allows users to only pay for the resources they use, making it a cost-effective solution for machine learning.

Security: Azure VMs provides several security features to protect your data and infrastructure, like Azure security center, Azure AD and Azure Key vault, which can help to secure your machine learning models.

Integration: Azure VMs can be easily integrated with other Azure services, such as Azure Machine Learning, Azure Databricks, and Azure Container Instances, which can help to simplify the machine learning workflow and improve collaboration.

High availability: Azure VMs can be deployed across multiple regions, which can help to ensure high availability and minimize downtime for machine learning workloads.

Step #2: Create a new Virtual Machine: Go to the navigation panel on the left side of your Dashboard and select Virtual Machine. Click on Add. This will open the panel to create a new Virtual Machine.  
Step #3: Setting up the properties of our Virtual Machine: We have to set certain properties of our Virtual Machine.

1) Select your Azure subscription. 2) Select the resource group. 3) Enter the name for the Virtual Machine.


4) Region: Cloud servers are placed at different locations. Choose the region closest to your current location. 5) Select the operating system as per your wish. 6) Size: Select the configurations such as RAM, number of CPUs, storage unit, etc. Select the most suitable configuration setting according to your requirements and budget.


7) Username: Enter the username for the Virtual Machine. Remember it as it will be required for logging into the Virtual Machine later. 8) Password: Enter the password for the Virtual Machine. Remember it as it will be required for logging into the Virtual Machine later. 9) Inbound Ports: Select all the inbound ports available in the options.

Left rest of the details as it is. Click on Next: Disks button. 

10) You can choose to use the SSD disk. Just select the Standard SSD option.

Left rest of the details as it is. Click on Review + Create button. 
Step #4: Validation and Creation of the Virtual Machine: After clicking on Review + Create button, Azure will validate the settings and will return error if found. Virtual Machines can be expensive. Microsoft charges hourly for the Virtual Machine. To save the cost, you can shut down the machine when you are not using it. 
Click on Create and wait for some time, your Virtual Machine will be created. Now we will connect to it using RDP. 
Step #5: Connecting to the Virtual Machine: After Virtual Machine is ready, click on Go To Resource button. 
Click on Connect button and download RDP file from the right panel. 
Open the RDP file and fill in the credentials to login. 
After this, you will be connected to your Virtual Machine. You can install the software, download packages and libraries, and can do any legal activity on this Virtual Machine. Disconnect from the Virtual Machine when you are not using it and stop it from its panel on Azure. In another article, we will cover some of the cool and exciting features that Azure Virtual Machine provides us.

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Last Updated : 02 Feb, 2023
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