Applications of Machine Learning
Artificial Intelligence and Machine Learning are among the most significant technological developments in recent history. Our lives, as we know it, like using machine learning products and tools, but many of the applications of machine learning technology go unseen.
Want to see some real examples of machine learning in action? Here are some ways that machine learning is changing the world.
Managing traffic
AI excels at managing logistics, and managing a city’s traffic is one of the most complicated and difficult pieces of logistics to understand. Millions of data points and thousands of commuters must be properly accounted for, in effort to ensure the trains run on time, traffic lights are functioning correctly, and maintenance is performed where and when it’s needed. In many modern cities, machine learning needs to be at the center of the transportation system. Data like rush hour fluctuations, road wear and tear, and existing maintenance schedules can be used to build powerful ML models. Ultimately, these models help improve traffic flow, increase the usage and efficiency of sustainable modes of transportation, and limit real-world disruption by modelling and visualizing future changes.
Making beer
Despite traditionally involving only three ingredients (water, barley, and hops), the art of brewing beer is a complicated and precise scientific process. The simplest change can dramatically affect the flavor and even ruin a batch — whether it’s the temperature of which it’s brewed or the amount of time the brew sits for. And that’s without considering the countless ingredients that are used in modern brewing techniques.
With machine learning algorithms, brewers can more easily make and keep track of these micro-adjustments to ensure flavor quality and consistency. ML can also be used to develop and refine new flavors by analyzing past popular and successful brews, as well as brews that failed or were less popular.
Sentiment analysis
Sentiment analysis is a real-time machine learning application that determines the emotion or opinion of the speaker or the writer. For instance, if someone has written a review or email, a sentiment analyzer will instantly find out the actual thought and tone of the text. This sentiment analysis application can are used to analyze a review-based website, decision-making applications, etc.
The applications of machine learning are endless and we have only begun to see some of the cool ways it will change the world. I think the examples in this article help to show its flexibility and how it can be used in ways that we wouldn’t imagine.
If you have any questions, please leave them in the comments below.
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