Top 7 Applications of Machine Learning

Top 7 Applications of Machine Learning

Being a subfield of artificial intelligence, machine learning helps machines operate more accurately. It ensures the machine carries out the required task efficiently and operates on its own. Machine learning algorithms rely on historical data to predict new results.

Users now rely on machine learning applications for spam filtering, fraud detection, malware threat detection, predictive maintenance, and business process automation. This technology is evolving with every passing year and getting better. Machine learning can one day make it possible for machines to operate fully autonomously.

People are already using machine learning applications without knowing how those apps work. Let’s learn about some top-trending applications of machine learning and their benefits.

● Speech recognition

All the new Android and iOS devices come with the “voice search” feature. Those devices not only recognize your voice but also follow your commands. It has been possible because of speech recognition. That is one of the leading machine learning applications.

Speech recognition transforms voice instructions into text. Some people also call it speech-to-text conversion. Modern devices and machines can do this task pretty efficiently. Speech recognition allows users to search for content on the internet without typing the text. If they speak clearly, smart watches, mobile phones, and PCs can recognize what you want and search for it for you.

Many web applications offer voice search features. We got virtual assistants, such as Amazon Alexa and Google Assistant. Those devices can handle many household tasks, such as turning devices on/off and controlling interior/exterior lighting and machines.

● Image recognition

Image recognition has become one of the most widely used applications of machine learning. Web apps and smart devices use this application to recognize objects, places, people, and digital images.

Social networking apps and websites, such as Facebook and Instagram, have been using the image recognition feature for the past few years. Those applications can easily recognize people present in pictures. You get suggestions to tag people present in your pictures and upload multiple pictures quickly.

● Product recommendations

Millions of people buy a variety of products online or offline. Most of them search for required products online. They visit many e-commerce platforms to find and assess many products in their budget range. The search engine learns from your searches and starts recommending products in the searched categories.

Many companies, such as Amazon, Disney+, Netflix, etc., are using product recommendation applications to find more buyers. This machine learning application is rapidly increasing sales made by various companies around the world.

People used to encounter irritating ads, but not anymore. Today’s cutting-edge applications and devices learn products you may like to buy. They filter ads according to your demands and assist you in buying the best products available. This application is consistently evolving and helping both buyers and business owners.

● Traffic prediction

Those days had long gone when people used to carry maps in their cars. Today’s travellers only need a fully-charged mobile phone to explore unknown regions. Applications, such as Google Maps, help users find the simplest route to their destination. Users can virtually explore various paths and choose the shortest route to the chosen destination.

The Google Maps application is capable of predicting traffic on the route. It can indicate whether the traffic is moving slowly, faster, or the route is heavily congested. Since most users around the world use Android devices, Google Maps tracks the real-time location of users. It uses past data and sensors to predict traffic.

● Malware and spam filtering

Email service providers are using the malware and spam filtering feature of machine learning to automatically filter spam messages and malware. This application can automatically detect and filter spam and normal messages.

Google’s Gmail can filter harmful spam and important messages and show them in different folders. Your inbox will get only essential emails. The spam folder will contain many ad emails sent by spammers.

This application of machine learning helps all email users. People do not realize its importance because they don’t need to go through numerous spam messages. This feature was not available a decade ago, and it was pretty irritating to filter unwanted messages at that time. Fortunately, machine learning has made things a lot simpler now.

● Self-driving vehicles

Self-driving cars are not fiction anymore. The world’s leading automobile companies are using machine learning to develop flawless programs to assist drivers. Those days are not too far when cars, trucks, and other vehicles will operate automatically. This technology is still new and requires major improvements. However, vehicles will get extremely sophisticated programs to recognize traffic, nearby vehicles, and the right path to the destination.

● Fraud detection

Machine learning has saved millions of people from online fraudsters. Its fraud detection application is making online transactions safer. Feed Forward Neural network can identify fake IDs, accounts, and suspicious platforms. It can check whether the transaction is genuine or fake. If it is fake, users receive alerts, and they can prevent fraudsters from stealing their funds.

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Conclusion

Artificial intelligence and machine learning technologies are still in their infancy period. Data scientists and machine learning experts are working tirelessly to improve existing applications and develop new programs to automate many procedures. Cutting-edge applications of machine learning will certainly help businesses, industries, and common people by making complex tasks much easier.

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