{"id":8043,"date":"2025-01-20T20:10:04","date_gmt":"2025-01-20T19:10:04","guid":{"rendered":"https:\/\/www.laresidenceabano.it\/what-is-machine-learning-and-why-is-it-important\/"},"modified":"2025-01-20T20:10:04","modified_gmt":"2025-01-20T19:10:04","slug":"what-is-machine-learning-and-why-is-it-important","status":"publish","type":"post","link":"https:\/\/www.laresidenceabano.it\/it\/what-is-machine-learning-and-why-is-it-important\/","title":{"rendered":"What is machine learning and why is it important?"},"content":{"rendered":"

Machine Learning: Algorithms, Real-World Applications and Research Directions SN Computer Science<\/h1>\n<\/p>\n

\"machine<\/p>\n

Since deep learning and machine learning tend to be used interchangeably, it\u2019s worth noting the nuances between the two. Machine learning, deep learning, and neural networks are all sub-fields of artificial intelligence. However, neural networks is actually a sub-field of machine learning, and deep learning is a sub-field of neural networks. Recommendation engines, for example, are used by e-commerce, social media and news organizations to suggest content based on a customer’s past behavior.<\/p>\n<\/p>\n

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machine learning importance<\/figure>\n

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Hence, autonomous vehicles are not bound to play the role of silver bullets, solving once and forever the vexing issue of traffic fatalities (Smith, 2018). Furthermore, the way decisions enacted could backfire in complex contexts to which the algorithms had no extrapolative power, is an unpredictable issue one has to deal with (Wallach and Allen, 2008; Yurtsever et al., 2020). As with all ML, an issue of transparency exists as no one knows what type of inference is drawn on the variables out of which the recidivism-risk score is estimated.<\/p>\n<\/p>\n

Big data<\/h2>\n<\/p>\n

By building ML into processes, leading organizations are increasing process efficiency by 30 percent or more while also increasing revenues by 5 to 10 percent. At one healthcare company, a predictive model classifying claims across different risk classes increased the number of claims paid automatically by 30 percent, decreasing manual effort by one-quarter. In addition, organizations can develop scalable and resilient processes that will unlock value for years to come. AI and machine learning provide a wide variety of benefits to both businesses and consumers. While consumers can expect more personalized services, businesses can expect reduced costs and higher operational efficiency.<\/p>\n<\/p>\n