How to Take Your Business on the Next Level with Microsoft Machine Learning Server

A great deal of technological research in recent years is going into making devices such as computers more intelligent. The idea behind it is to equip them with capabilities similar to human cognitive abilities.

Taking place under the collective branch of artificial intelligence (AI), the field has lots of sub-branches, one of which is machine learning. To understand the meaning of machine learning, consider the conventional computer program design.

The traditional program remains the same over the years and is incapable of learning from history and available data. But thanks to machine learning, computer programs can now use a combination of history and data, new and old to learn and adapt to different circumstances.

For businesses, this is invaluable as it comes in handy in tailoring solutions for specific customers. Happy customers translate to higher satisfaction and subsequently, better customer loyalty. Executives are also better able to use available data to draw insights, predict trends and create strategies to enhance performance.

Introducing the Microsoft Machine Learning Server for Businesses

In spite of its obvious benefits, machine learning adoption is a slow and arduous process. Not only does it require a heavy investment in capital and a skilled labor force but it also requires tons of time for amassing data, building machine learning algorithms, training models and much more. And these necessary tasks are not within reach for many small and medium-size businesses. This is where the Microsoft Machine Learning Server comes in.  

Microsoft Machine Learning Server refers to a machine learning as a Service (MLaaS) solution that offers off the shelf packages for enterprises to meet their existing needs. The solution consists of a set of tools and services designed specifically for businesses looking to jump on the machine learning bandwagon.

Versatility is one of the highlights of its design, as it aims to meet the needs of a wide array of users. At the moment, a majority of Microsoft products including Office 365, Windows 10, Azure and others already incorporate machine learning abilities.

The Machine Learning Server, however, takes it a notch higher by incorporating significant AI capabilities. It offers full support for Python and R. Its support for Python covers the entire lifecycle of data science in Python-related analytics. On the other hand, its support for R combines a legacy of Microsoft R Server 9x and Revolution R Enterprise products.

Practical Applications of Microsoft Machine Learning Server Solutions for Your Business

  • On-Premise Machine Learning

It is possible to deploy the solution at your data center. The server supports the use of distributed Python- and R-based machine learning solutions at scale. You can deploy the solution on-premise so as to facilitate the use of machine learning technology for relational data.

It also supports the visualization of data from other databases, on-premise, and also from HDFS Data Lake where machine learning training will take place.

  • For Cloud-Based Platforms

If your business has already embraced cloud-based operations, you can use the solution to speed things up. Its Azure machine learning service is a managed cloud solution that facilitates the building, training and deployment of models using Python and CLI from the cloud to the edge.

Harnessing the power of the cloud combined with machine learning makes it possible to build much better models a lot faster than using any traditional approach. And as soon as the models are ready for deployment, you can do so using containers to various relevant services.

Considering that a majority of data science tools on Azure are pre-installed and pre-configured, hosting it makes plenty of business sense. You can use it to monitor model performance then retrain to meet requirements. And if you need cognitive abilities on your app, you can access the required Azure cognitive services right in the package.

  • Data Experimentation without Data Science Qualifications

If you are thinking of exploring the technology in-depth before deployment, it also offers the relevant platforms for such experimentation. For instance, the Microsoft Azure Machine Learning Studio, a GUI-based tool with drag-and-drop functionality offers boundless potential.

It is, in fact, a great starting point if you are just getting started on the technology since it’s a useful platform that can help you understand how to build algorithms, test and deploy them. For data scientists, it can also provide the ideal environment for exploration prior to building custom solutions.

  • Deployment of Prediction Services

The Machine Learning Server comes complete with a sophisticated framework that allows for the deployment of prediction models. When defining prediction services, you simply need to upload a model together with a script to a database.

From there on, the service will handle all manner of batch requests without the need for any further input on your part.

Benefits of Microsoft Machine Learning Server for Your Business

By virtue of the ease of deployment of these solutions, you do not necessarily have to have a data science degree so as to leverage the opportunity. Under the packages, you can access lots of built-in algorithms using which you can create an end-to-end machine learning-based solution.

Besides the easy deployment, there are lots of other benefits that business operators can access from the solution.

  • Optimizing Operationalization

Thanks to the solution’s support for operationalization, the platform allows model deployment to the scalable grid for batch and real-time scoring. Currently, enterprises that use legacy operationalization solutions face a number of challenges.

Among these is the fact that they have to contend with outrageous costs and unexplained delays. These result from the time and resources that go into model translation, iterations to ensure validity, addressing regulatory issues and other efforts to manage permissions and keep models relevant.

But by choosing the Microsoft Machine Learning Server, they are able to access optimal operationalization. Often, all they need is a click here and there for the creation of APIs for web service support. The solution hosts web services on an on-site or cloud server grid which you can integrate with line of business applications.

  • Maximizing Data Security

Enterprises today have access to more data than ever before. While this aids decision making, it also poses challenges. For instance, with the passing of time, such data can spread across multiple platforms.

It thus becomes difficult to find ways to bring machine learning solutions to the different platforms where data resides. The Machine Learning Server solution for this is bringing machine learning to where the data is rather than the other way around. This reduces the chances of data getting compromised while on transit between various points. It also reduces wastage of resources.

Finding Your Business Fit

Regardless of your background and your unique business needs, Microsoft has rolled out versatile features to allow you to integrate machine learning with ease. The aforementioned applications of the solution in your business are just a tip of the iceberg in as far as the potential of the technology is concerned.

All you need to do is to define your business needs and identify the relevant solution. You have the option of taking advantage of pre-trained models or training your own custom model with ease. Depending on whether you are just starting out on data science, are in the heart of it or have a team of developers with technical know-how, Microsoft Machine Learning Server has something stored for everyone.

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Janica San Juan

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