You have probably heard a lot about AI (artificial intelligence) and automation. However, you may not have heard of a closely related technical field; machine learning. Machine learning refers to the way algorithms can be programmed to analyze enormous amounts of data and statistics in order to detect patterns. These patterns can then be used to carry out further automated processes. Examples of Machine Learning
One prominent example of machine learning that you are likely to encounter every day is that of search engines. Google makes heavy use of machine learning in order to provide results. But what other examples of machine learning are there? This article will explore six of them.
Self-Driving Vehicles
One of the most well-known (and controversial) examples of technology-driven by machine learning is that of self-driving cars. These autonomous vehicles are driven (in both senses of the word) by complex algorithms that are continuously refined over time. These algorithms enable vehicles to gather various data on their surroundings and automatically choose a course of action. This has divided opinion, especially when it comes to tough dilemmas such as deciding which vehicles to collide within an unavoidable crash.
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Image Recognition
Machine learning is an important component of image recognition technology. Algorithms are used to separate images into various categories based on previous identifications. These algorithms get more and more accurate with the more identifications they make.
Speech Recognition
Similar to image recognition, speech recognition is powered by machine learning. The examples that most of us are likely to be familiar with are smart speakers and programs such as Apple’s Siri or Amazon’s Alexa. Speech recognition technology is all about learning who is speaking and understanding their personal speech patterns over time.
Fraud Detection
Fraud detection is a particular area where machine learning has been proven to be more effective than a human. This technology is used by banks, retail stores, government agencies, and many more organizations. Algorithms are programmed to notice patterns of user activity that have historically indicated fraud, and flag this as potentially fraudulent activity. If you want to learn more about machine learning and how it can help your business avoid user fraud, you can take an AWS machine learning certification path course.
Recommendations
How many times a day does technology recommend a product or service to you? The answer is probably higher than you would expect. As well as “Recommended for You” sections on sites such as YouTube, Netflix, Amazon, and many others, sites also often personalize their homepages to the specific user. Recommendations are carried out by algorithms that analyze your past activity, purchase history, and feedback on particular products or pieces of content.
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Banking and Finance
Banks and other financial institutions make extensive use of machine learning in order to calculate a number of money-related issues. For example, Forex and cryptocurrency stock trading platforms use machine learning algorithms to make predictions. Banking accounts also use algorithms to come to decisions regarding services such as overdrafts and which users should and should not be permitted to use them based on their account history.
Would you like to read more about Machine Learning-related articles? If so, we invite you to take a look at our other tech topics before you leave!
