Machine learning, along with many other disciplines within the field of artificial intelligence and cognitive systems, is gaining popularity, and it may in the not so distant future have a colossal impact on the software industry, and the way businesses operate.
In a recently published article entitled, “Machine Learning: The Real Business Intelligence,” author and expert, Kai Goerlich, writes:
“Business intelligence (BI) tools first appeared on the enterprise technology scene several decades ago, at birth clumsy and difficult to use but ultimately improving the flow of data through organizations from their operational systems to decision support,” adding, “Increased data-processing power, the availability of big data, the Internet of Things, and improvements in algorithms are converging to power this actual business intelligence. To be clear, this will be an evolution rather than a revolution.”
In simple terms, machine learning is a branch of the larger discipline of Artificial Intelligence, which involves the design and construction of computer applications or systems that are able to learn based on their data inputs and/or outputs.
“Artificial intelligence (AI), a term dating back to the 1960s, is tossed about quite a bit these days. It’s an umbrella descriptor that refers to computers capable of doing things that a human typically would. It’s often inaccurately used interchangeably with machine learning,” Goerlich writes, adding that machine learning is a specific subset of AI that uses statistical methods to improve the performance of a system over time. “Any programmer can write code to develop a program that more or less acts like a human. But it’s not machine learning unless the systems is learning to how to behave based on data.”
So how can machine learning and AI tools be beneficial for business processes?
In an article entitled, “What is Machine Learning and How Can It Benefit Your Business,” author, Lillian Pierson, outlines how below:
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Build more accurate pricing models
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Detect network intrusions
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Generate real-time targeted advertising on websites
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Reach record sales via recommendation engine deployment
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Improve demand forecasts in retail
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Detect and prevent fraud in real-time
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