Write 2.5 and add 18 zeros. That’s the amount of data generated on a daily basis (theBig Data). By the way, that number is called 2.5 quintillions, and since we are talking about data, we’ll use bytes as the measuring unit of data.
With such a hefty amount of data, it wasn’t possible for the computing devices to interpret Big Data and make something useful out of it. The traditional way ofdata processingwasn’t enough to handle that colossal amount of unstructured data until a computer scientist and cognitive psychologist, Geoffrey Hinton, used his expertise in neural networks to work on what’s known as Machine Learningtoday.
What is Machine Learning (ML)?
Machine Learning is a division ofArtificial Intelligence(AI) that DOES NOT use explicit programming to generate results. That means that once you feed a program with the basic input, you will start getting results based on the primary input.
Since the world is generating so much data and there’s no reduction expected in the next 5-10 years, instead of that, the data generated will increase by 12-14%. So how will large-scale businesses cope with such a situation?
Here comes the role of ML in dealing with Big Data. To store the huge unstructured data, we have storage devices to do. Businesses don’t hesitate to invest in storing but reading and extracting useful information from that large collection of unorganized data. The data scientists are well-qualified, no doubt, but to find the criticality and give something productive to the company is what matters the most. And when it comes to processing all that, there are programs that use ML to do the following tasks:
- Manage unstructured data
- Eliminate useless data
- Record useful data
- Discover key patterns
- Analyze the data
- Give evaluation
Let’s understand this technology with an example.
Machine Learning in Online Businesses
The trend of online shopping and transactions is at its peak. People have found out that e-commerce has really eased their shopping experience. By giving them cost-less virtual shopping mall visits and the facility to pay online, people are now spending a good time finding their desired items on particular websites. While they are scrolling hither and tither, an AI-based software is analyzing their activity online and gathering what they are doing. Here, you have to accept that your online activities are never hidden. Companies silently gather such data and apply ML algorithms to get a pattern of your browsing and buying behavior. Hence ML is a dominating factor that allows totally unrelated ads to haunt you.
That’s a common example of how online businesses are retaining customers.
Machine Learning in AI-based Devices
Summery
AI gave birth to ML through which a large amount of unstructured data (Big Data) is interpreted. With such data interpretation, ML gives useful information from that data by eliminating futile elements. The information is then used to make productive decisions for the growth of the online business. Numerous industries have adapted AI-based business operations, and they now use ML programs to predict what step to take in the future.