Machine Learning

4 Everyday Examples of Machine Learning

Machine learning may sound futuristic, but it is something that most people encounter every day. When you use voice recognition to speak to your phone, turn to a reliable app for directions, or chat online with a virtual assistant, you are utilizing this technology. If you have ever wondered how Facebook is so good at showing you ads you are interested in, you can also thank machine learning. 

Machine learning is the process through which computers analyze large amounts of data to draw increasingly improved conclusions. As the machine gathers more information, its predictions become better because it is learning every day.

Voice Recognition

Voice Recognition

Image via Unsplash by Andres Urena

Speech recognition is one of the earliest applications of machine learning. IBM introduced the first speech recognition machine in 1962. Today, we enjoy the conveniences of voice recognition every time we speak to Siri, Alexa, or Google. These programs get progressively better at recognizing our voices each time we speak to them. Sometimes, they will even ask for clarification so they can improve in the future.

Traffic Predictions

The days of paper maps spread haphazardly across the dashboard of your car are long gone. Navigation apps deliver turn-by-turn directions neatly and efficiently, making it easier than ever to reach new destinations. In addition to directions, most applications offer an estimated arrival time as well. To deliver this detail, the program must use traffic-flow prediction. Machine learning makes it possible for systems to correlate traffic flow measurements over time. Predictions are then compared to real-time data for accuracy, and the algorithms are continuously adjusted to provide ever-improving results.

Virtual Assistants

Machine learning equips virtual assistants to deliver keenly personalized services. By gathering data from previous activities, schedules, queries, and messages, virtual assistants can begin to assemble a profile for the individual user. Using this information, the assistant may recommend restaurants that you are likely to enjoy, suggest reminders for recurring activities, and accurately interpret your own unique shorthand. 

Chatbots can learn to understand the intent of comments, even when it is not direct. The longer you work with a virtual assistant, the better it will become at understanding everything from your sleep habits to your taste in entertainment, giving it the information it needs to deliver personalized recommendations that are relevant to nearly every part of your life.

Product Recommendations

Marketers are keen to use machine learning to help them better reach their target audience. Machine learning programs evaluate your purchase history, browsing history, and interests to paint to picture of who you are and how you shop. These programs compare your statistics with those of other shoppers to identify key correlations. For example, machine learning can help a company realize that women who buy a particular shoe are more likely to also purchase a certain dress. With this information in hand, companies can deliver targeted product recommendations that may actually slow your scroll and inspire a purchase. Machine learning turns computer programs into continuously evolving applications that improve with use. This is one of the most powerful ways to move technology forward and provide personalized solutions to customers. The opportunities are nearly endless.

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