Create Deep Learning Models On Azure Data Science Virtual Machines
As a developer in the current scenario, it is important to know how to build easy models of deep learning. If you are eager to build your own models, but not sure where to start then you are at the right place.
With the new deep learning course from fast.ai, you can create your own deep learning data science models.
With this course, you will become efficient in various techniques of deep earning. It will help you to made models for the same in multiple domains.
Also, for a better understanding of the subject, you should also learn Azure Data Science Virtual Machine (DSVM). It will enable a developer to create the best models by providing you with the tools that you need for the fast.ai course. It will help you use the course without having to go through any setup.
In this blog, first, we will learn a bit about deep learning. After that, we will see how Windows Azure Development tool DSVM and fast.ai help us with creating deep learning models.
Deep learning- An Introduction
Before we learn how to use Azure Data Science Virtual Machine to run fast.ai to learn DI, let’s learn what is it?
Deep Learning is a technique of Machine Learning through which computer gains knowledge about how to learn by example. It the key behind driverless cars, using deep learning models, owners can command cars to stop and so on.
It also the technique behind voice control in various devices like phones, TVs and so on. Lately, its models are in much demand, and they learn to complete a classification task through images, text or sound. Its performance is higher than anything humans can accomplish.
Deep learning theory came into existence in 1980, but it is getting popular now because:
- It requires a huge amount of labeled data and,
- It also requires strong computing power. For that, they need high-performance GPUs as they have a parallel architecture which is efficient for deep learning.
The deep learning models are used in various industries like:
- Automated Driver: Researchers are using models of deep learning to detect objects like stop signs and so on. It also helps detect pedestrians leading to a decrease in accidents.
- Aerospace and Defense: It identifies objects with the help of satellites so that troops can identify safe or unsafe zones.
- Medical Science: It is used by researchers to detect cancer cells by teams at UCLA.
How To Run The Fast.Ai Deep Learning Course On Azure DSVM?
Azure provides various ways for you to learn deep learning. But the best and easiest way is to use the Azure Data Science Virtual Machine. Azure’s DSVM is virtual machine images family. It has an inbuilt rich set of tools and framework for data science, deep and machine learning.
With Azure DSVM, you can save time on installing and troubleshooting any issue as you can utilize tools like Jupyter notebook. Both Linux and Windows editions offer this service of Azure.
Microsoft Azure specially provides an extension for the fast.ai course. It makes the whole proves simple and time-efficient.
Steps Of Getting Started With Azure DSVM And Fast.ai
The steps to start learning fast.ai deep learning course are pretty simple:
Register for Azure Subscription
You can register for Azure subscription or for Azure free trial subscription of 30 days. The free trial will let you explore and access many popular services for 12 months. The free trial subscription won’t let the developers access the GPU resources. For this, you have to sign up and pay or use Azure credits from Visual Studio subscription if you have any. Now, after gaining subscription, log in to Azure portal.
Create a DSVM instance using the fast.ai extension
After logging in, you can make data science virtual machine with the help of a fast.ai extension. You can do this by selecting any one of the given links:
1. Linux (Ubuntu) edition of DSVM with fast.ai
2. Windows Server 2016 edition of DSVM with fast.ai
In about five to ten minutes, it will create your virtual machine once you answer some questions in the deployment form. Also, everything you require from the course comes with it.
While creating deep learning or data science model, you can choose between a GPU or CPU based instance. If you use the GPU model, it will save time when you will train deep learning models.
Start running your course notebook
After creating your Azure data science virtual machine, you can instantly start t run your course in the code. It will give you access to the pre-loaded course and more.
Limitations Of Deep Learning Model
This is how Azure Data Science Virtual Machine helps you to make deep learning models. It is pretty simple and straight-forward. Moreover, with the help of Azure Machine Learning services, you can keep studying about data science and ML. It will also enable you to monitor your experiments.
At Microsoft, you will find various documents that can help further with automated machine learning and so on.
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