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Azure Machine Learning

Jul 04, 2017 Parth Patel

Azure Machine Learning platform was released on February 2015 allowing Microsoft to take advantage of Big Data, Cloud and Processing Power in one go.

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What kind of AI is Machine Learning?
Machine learning is simply a type of AI that will form and predict calculations based on your data. We all know that working with math and numbers mean that 99% of the time there’s a pattern associated with it. Using this assumption, let’s look at an example of how machine learning can help businesses.
Let’s say I have data of items that sold in the past 5 years:

          ⦁ Type of item
          ⦁ Date of sale
          ⦁ Forecast data

So with this information, the machine learning AI will generate some ‘patterns’. Here, ‘patterns’ mean that the program can give me estimates on sales for the next month or even the next year. With these estimates, I can plan my production, sales etc. thus making the best use of all my resources.

What does Azure have to do with Machine Learning?

As most of you already know, Azure provides a collection of cloud based services.
With Azure Machine Learning, you can use this technology right now on the cloud without investing in it individually. Microsoft has made it conveniently accessible through a browser.



Making it work / Getting started
With just your browser, you can navigate this amazing technology. Simply log on to Azure Machine Learning, and choose a plan that works for you. You will then be redirected to the Azure Machine Learning Studio. This is where you will import your data and build your own algorithms based on it.

You can choose from a wide range of options such as: data format conversions, data I/O, data transformations, R Language and Python modules so you can write your own custom code, web service so you can import your own web service inside of the algorithm, and at the core are the benefits of the options using machine learning.
With the machine learning options, you have access to 4 core functionalities you can place in your algorithm:

          ⦁ Evaluate 
          ⦁ Initialize Model
          ⦁ Score
          ⦁ Train

The tool has a flow chart kind of feel to it making it very user friendly.

Look at the example below:


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“Azure Machine Learning helps you find the pattern in the data and then use the results to gain useful insights.”

  • Sam Yehya
  • Vice President
  • Six Consulting, Inc.

increase in Azure sales (2020)

$36.9 billion

revenue (2020)

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