Machine learning is the idea that systems can learn how to make decisions with limited human interference. By identifying patterns, computers can learn from existing data without having to be programmed for each specific task. As new information is introduced, the systems adapt by referencing previous computations. This allows the machine to produce results with little to no ongoing interaction with humans. Even though machine learning programs have been in existence for a long time, in recent years they have become faster and more powerful. This had led many organizations to rely on them more heavily for tasks that may have, in the past, needed more human interaction. While some find the prospect of machine learning to be frightening, there are many great benefits to be gained from using this technology (4). Most of us have already been exposed to machine learning without even knowing it. The best example of this is the face tagging that is used by Facebook (6). Since the technology is here and not likely going away, it is beneficial to embrace these benefits and learn to integrate technology into daily living. It is important to understand the benefits that this machine learning can offer to our daily lives – especially within a business setting (4).
Smart Solutions for a Smart World?
There are many different industries that greatly benefit from the use of machine learning. The machines are used to do advanced calculations and to create models in a much more accurate and efficient manner than humans can manage. In this sense, it is beneficial for people to embrace this technology and learn to use it to help advance the productivity and quality of life. While the technology is ever expanding and changing over time, we can already see the benefits that have been demonstrated in the areas of financial services, government, health care, marketing and sales, and transportation.
With the increase in the number of payment channels (credit/debit cards, smartphones, kiosks), the risk of fraud has increased. This has made it more difficult for businesses to authenticate transactions. This is where machine learning steps in (2). Since machines are much better at processing large amounts of information, they are able to quickly recognize unusual purchasing patterns and detect potential fraud quicker than humans (2). In the area of financial services, machine learning can be greatly beneficial when considering portfolio management (identifying investment opportunities) and loan underwriting but, more importantly, it is useful in the area of fraud detection (4)(5).
As any government worker can attest, there is more paper work and case files to manage than is possible for the number of workers. Today governmental agencies are so vast and complicated that they need elaborate systems to help organize all of the data that they have to manage Machine learning can help with mining information for various useful insights about efficiency as well as fraud detection (4). Though there are many examples of how machine learning is used in a government setting, one time saving development that we can see on the U.S. Army website is an interactive virtual assistant which is able to do the work of 55 recruiters. This is an amazing development which frees up the time of these recruiters to do other tasks (1).
Machine learning is quickly growing and expanding in the health care field. New advances are being made regularly. With the development of wearable devices and sensors that can gather helpful information about patients in real time, we can really see the potential health benefits in various different settings (4). These wearable monitors are currently being used by the Army to determine the seriousness of wounds. This helps medical professionals to prioritize treatment (1). In the future, this type of technology will be used more broadly and will help improve the level of care that all patients receive.
Marketing and Sales
Machine learning can be used in marketing by modifying targeted ads based on customer behavior patterns. This can help a company become more efficient with their resources. This allows companies to know what products various consumers prefer and to be able to present the appropriate offers to these consumers (5). An example that we see regularly of retail businesses using machine learning is when a website recommends items for you that you might like based on previous purchases (4).
The goal of efficient transportation services is to maintain predictable routes that run smoothly with few problems. Machine learning can help with analyzing the data that is gathered thereby creating a more efficient and profitable system. By recognizing patterns and potential trouble spots, machines can learn when to suggest alternate routes and to predict waiting times (4).
Inside Machine Learning
While there are many different types of machine learning, the two most widely used are supervised and unsupervised learning. While both of these methods use algorithms, there purposes and capabilities are different(4).
In supervised learning, the algorithms are trained or taught by using data that is labeled. This algorithm receives input along with the desired output and it learns to modify the model according to that information. This type of machine learning is used in situations where historical data is likely to predict future behavior (4).
In unsupervised learning, there is no previously compiled data. The system is not given the answers. The algorithm, in this case, will explore a set of data and find a structure or pattern in it. This type of learning works for transactional situations and can be used to gauge which customers (for example) should be targeted for particular ad campaigns (4).
Why is Machine Learning So Important
The goal of machine learning is to understand the structure of the data and to use this to meet the goal of the organization. As we have noted, machine learning is used in various different industries including, but not limited to, financial services, government, health care, marketing and sales, and transportation. Machine learning can produce thousands of usable and beneficial models in the same time that humans can produce only one or two. This is a huge advantage in the advancement of efficiency and proper use of resources. With the progress that we have already seen in this area, the future looks bright for the expansion and further development of machine learning (4).
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Local Government News Articles. N.p., n.d. Web. 14 Mar. 2018. <http://www.govtech.com/computing/5-Ways-Artificial-Intelligence-Is-Already-Changing-Government.html>.
2. “How Machine Learning Facilitates Fraud Detection?” N.p., n.d. Web. <https://www.marutitech.com/machine-learning-fraud-detection/>.
3. Lejlic, Emir. “The Advantages of Machine Learning.” Lumagate – We Drive Business Evolution Forward. N.p., n.d. Web. 13 Mar. 2018. <https://www.lumagate.com/news/the-advantages-of-machine-learning>.
4. “Machine Learning: What It Is and Why It Matters.” What It Is and Why It Matters | SAS. N.p., n.d. Web. 13 Mar. 2018. <https://www.sas.com/en_us/insights/analytics/machine-learning.html>.
5. “Top 8 Business Benefits of Machine Learning – Outsource2india.” Outsource to India. N.p., n.d. Web. <https://www.outsource2india.com/software/articles/businesses-benefits-machine-learning.asp>.
6. “The Value of Machine Learning: Benefits and Best Practices.” DATAVERSITY. N.p., 30 May 2017. Web. 13 Mar. 2018. <http://www.dataversity.net/value-machine-learning-benefits-best-practices/>.