Machine Learning and its Real-Life Applications

Machine Learning and its real life applications

With everything coming into the scope of automation, technology has certainly taken over a multitude of sectors in life. The idea of everything being at your fingertips is a reality. Technology takes over and software development can be seen as revolutionizing business methodologies everywhere allowing them a choice of customization that they never had access to before!

Businesses have eventually come to the realization that nothing supersedes the impact of customer acquisition and retention as well as a user-friendly and preference customized solution offered by them. With this awareness came the high rise in the demand for digital improvements and in-depth AI integration within systems of the companies and strategies of the sales funnel. Today, mobile platforms can be seen being utilized in every business industry to maximize the user experience and this has further expanded the mobile app development industry.

The Incredible Realm of Machine Learning

ML is fundamentally all about extracting relevant and valuable information from the given data. It is a technique in programming that offers the strength to an app to make automated analysis and improvement in its functionality based on experience. Software development certainly takes advantage of ML resources throughout their lifecycle. Data, in this sense, could contain varied things; it could be of anything ranging from video, images, sound, text, sensor data, and whatnot. The usual run-of-the-mill ML solutions could vary in models that examine, analyze and classify video and images; whereby, the example of ML applications being able to observe the well-being of compound industrial equipment via sensor data or foretell the prediction of the future sales for your business is just one face of this incredible scenario.

Real-Life Applications of Machine Learning

Believe it or not – this is the future, Artificial intelligence (AI) and Machine learning (ML) is spearheading the modern technological-race of the world. Empowering the businesses with the ability to offer customer support, customized product

service features to applications, and entertainment that stays as an incentive for app usage for the user, ML continues to grow stronger promising incredible solutions that seem like a dream today.

Here are some sectors that can be witnessed using ML, at a big scale throughout the globe:

  1. Financial sector
  2. Government Sector
  3. Healthcare Sector
  4. Consumer Goods
  5. Manufacturing Sector
  6. Education Sector
  7. Media
  8. Retail Marketing

Let us take a look at some of the application categories of ML.

Image Recognition

Image recognition is an approach for detecting and identifying a trait, feature or an object in the digital image. The market of image recognition is expected to reach USD 38.9 billion by 2021 as researched by Market & Markets. It is a simple yet effective methodology – that can be seen enabling the mobile app development niche to grow their product range, offering advance security and accessibility customization for their clients. Some of the image recognition mobile apps are Google Lens, Tap Tapsee, Image Teller, Cam finds, Flow powered by Amazon, etc.

Sentiment Analysis

Sentiment analysis is an application that has dramatically changed the business marketing scenario as it refers to a process of automation whereby behaviors and reviews are extracted for a subject matter. It is integrated with the purpose of accumulating data that can be used to improve service and product functionality for the users. The sentiment’s analytical usage is expected to grow up to USD 6 billion by 2023, as forecasted by Market Research Future in their report.

The utilization of this methodology of ML with the star rating system can be seen integrated with the CEM of a variety of business apps. Apps for any industry is bound to have a review section that collects user responses and behaviors, translated through further ML to make the due improvements.

Speech Recognition

Speech recognition is the method of altering spoken words into the text form. Also known as computer speech recognition or speech to text, speech recognition is the latest area that is benefited from big data and ML.  The speech recognition application can also be used for additional analysis that is in educational, military, and health care.

Email Classification and Spam Filtering

Machine Learning algorithm is also being employed to arrange and filter a huge lot of spam. Several methods are incorporated to filter such as C4.5, multi-layer perception, among others. Where filtering through a rule-based has numerous downsides, the ML method to filter out the spam is more orderly and organized. 

ML has come up with brilliant solutions that have enabled the business industries to reduce cost, increase efficiency and scale profits – all at once. As of now, the ML is being forecasted as the era of ML superseding all. This is not the end but a beginning for Machine Learning.

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