Amazon’s AWS and Microsoft’s Azure are the two major players in the cloud computing industry. Both of these behemoths of the IT world are constantly looking to change the game by launching useful and feature-filled software periodically. Launching Azure Machine Learning Studio by Microsoft has been an initiative in the right direction, and it has succeeded in bringing in additional users from all around the world. After the phenomenal reception of the Hadoop-based Azure HDInsight and PowerBI for Office 365, Azure Machine Learning is the next step by Microsoft towards market leadership in Big Data. The fact that this service is available on the cloud platform makes it all the more appealing to the end-users.
Extremely powerful machine learning languages, like Python, are receiving continued support in the Azure Machine Learning Studio. As most data scientists depend heavily on Azure for most of their tasks, the Azure Machine Learning Studio has become an integral part of their day to day operations. Azure Machine Learning Studio supports integrating Python scripts into different parts of a machine learning experiment and also helps in publishing them as web services on Microsoft Azure.
Many people have reviewed Azure Machine Learning Studio since its launch and it has passed with flying colors in most analysis. Azure's machine learning services are much easier to learn than offerings on some competing cloud platforms. Microsoft’s solution is targeted at enterprise and platform-as-a-service model. It is more suited for those businesses that want to take less responsibility for managing the underlying infrastructure.
Features that Make Azure Machine Learning Studio Special
The many features of the Azure Machine Learning Studio are as follows:
Support For R Scripts
People, who like to write code instead of building experiments from multiple blocks, have the option to prepare data by writing R scripts. In case, R package is not available by default, it is possible to upload it to the experiment by yourself.
Support For A Variety Of Data Mining Algorithms
Ensemble models, such as Boosted Decision Trees are supported by Azure Machine Learning Studio.
Drag And Drop Approach For Building Experiments
This unique feature provides ability to save a trained model and reuse it in different experiments. In addition to the functionality it offers, it looks very nice.
Valuable Documentation And Better Text Analytic Support
This is one of the most underrated features of AMLS, however, it helps a great deal in enhancing your knowledge of this domain.
Advantages of Using Azure Machine Learning for Small and Medium Businesses
If you are an entrepreneur who deals with AI and Big Data, then using Azure Machine Learning Studio can offer you a great advantage over your competitors:
Machine learning Service
When you are using Azure Machine Learning, you do not have to procure software solutions and bear the burden of creating complex infrastructure. You can pay as you use the Azure cloud services and reap in rich dividends over a period of time.
Easy to Use Algorithms
There is no need to perform complex calculations or hand-calculate a decision tree. All you need to do is to know when you might want to use one over the other.
Convenient to Design a Web Service Front End
After testing a machine learning experiment, you can simply push a button and the AMLS will create a web service based on your experiment. It will allow any application with valid credentials to pass in data and retrieve a result.
Better GUI
Compared to other solutions for Big Data and data mining, the Azure boasts of a better GUI that can help you perform complex tasks with ease.
Leverage your Business with Azure Machine Learning Studio
The aforementioned Azure Machine Learning Studio review has clearly showed that it is an amazing technology with great potential that needs to be tapped into for great rewards. If you already have a workforce with programming experience using R and knowledge of common statistical methods and data analysis, you can enroll them in QuickStart’s Azure Machine Learning course for improving their knowledge. With the right guidance, they would be able to deploy, configure, operate, and manage all aspects of Azure Machine Learning Studio and add value to your business.