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How Microsoft Applications Use Machine Learning to Make You More Efficient

Machine Learning

If you use Microsoft Office, you must have lately noticed several changes in almost every application of the software suite. Microsoft Word now suggests better words or phrases; Outlook offers improved assistance while you write an email; you get AI-based help while designing PowerPoint slides. Microsoft has ramped up machine learning development for its Office 365 (now Microsoft 365) applications. All these features are based on Microsoft Azure machine learning.

Microsoft is constantly upgrading all these features and improving its machine learning capabilities even more. Also, the software behemoth recently renamed its most popular suite Office 365 to Microsoft 365. Microsoft promises to offer additional features and benefits to the subscribers. For instance, Microsoft 365 features intelligent writing assistance in documents, emails, websites, etc. Its AI and machine learning-based assistant Microsoft Editor has evolved remarkably. Software companies have benefited greatly from Microsoft Office 365 Collaboration and other such initiatives.

Machine Learning Capabilities in Microsoft Applications

Microsoft subscribers have access to the intelligent writing assistance, Microsoft Editor. This ML-based tool suggests you better phrase, grammatical errors, conciseness, and readability, among others, while you type. These features are a lot like writing assistance tools like Grammarly. But these are all built-in on Microsoft software applications.

Azure machine learning capabilities enable Microsoft to use real-world number comparison. This has been used by the Bing browser for a while now. Artificial intelligence, combined with machine learning development, makes the incorporation of such features easier and more efficient. For example, Word can even recognize that the heading phrase bold and suggest a heading style.

The emailing application Outlook uses machine learning on iOS to suggest you when to read an email. It can also readout your message. Besides, Outlook uses machine learning and natural language processing (NLP) to suggest quick replies to the emails you receive. These replies may include a “looking forward to it,” or a meeting schedule. Programming methods like Python development let developers to efficiently incorporate such features onto software applications.

Excel also uses NLP for spreadsheets. It enables you to ask questions about your Excel data. Machine learning capabilities in PowerPoint Designer can do many useful things for you. It leverages ML for text and analyzing slide structure. Additionally, the Presented Coach guides you to overcome problems like slouching, or talking in a monotone, or staring constantly at the screen while you present. The tool analyzes your voice and body posture using machine learning techniques.

Easy-to-use ML to Make You More Productive

Most of the machine learning capabilities offered by Microsoft applications are built using the Azure machine learning service. Features like in-built Azure Cognitive Services APIs allow developers to build functionalities like speech recognition. Many other features are based on machine learning development models like Turing Neural Language Generation. It is a deep learning language model that has the capabilities of learning answering questions and completing sentences, among other things.

The Azure Machine Learning platform enables both Microsoft and its partners to develop software solutions with intelligent features. It renders automation, processes data, and feeds the information into training the applications. These advanced machine learning and AI-based features have helped Microsoft Office 365 Collaboration partners to build intelligent software solutions. As Microsoft keeps upgrading its ML techniques, we can expect more productivity-focused features in the future.

Conclusion

Machine learning capabilities make your software application much more useful than a traditional solution. Microsoft enterprise software solutions are designed to help businesses and software developers to enhance productivity. At OrangeMantra, we use a diverse range of Microsoft services and solutions to build intelligent software applications. Our clients count on us for feature-rich enterprise solutions that make business operations more efficient and profitable. Machine learning not just enables you to improve business productivity but also lets you better understand customers. With increasing competition across industries, AI and ML-based software solutions are going to become mainstream in the coming times.

FAQs

Q. How is machine learning used?

Machine learning (ML) algorithms look for natural patterns in data that generate insight. The use of ML helps you make better decisions and predictions. They are used every day to build intelligent solutions, make critical decisions in medical diagnosis, energy load forecasting, and more.

Q. What is the best programming language for machine learning?

Python is the most popular general-purpose programming language used for machine learning development. R is used for data analysis and statistical computations. The efficiency of the language for machine learning depends on the area on which it is going to be applied.

Q. What is Microsoft Azure used for?

Azure is a public cloud computing platform—with solutions including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It is also used for machine learning techniques, and other services such as analytics, virtual computing, and networking.

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