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Read Time:2 Minute, 25 Second
  • Business

What is machine learning? Definition and examples

On 3 years Ago
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Machine learning is an application of artificial intelligence  that gives “smart” machines the ability to learn and improve automatically. They improve with experience, even if computer scientists don’t explicitly program them  for certain tasks. 

The term refers to the development of software engineering that allows machines to access data and then use that data to learn on their own. In other words, learn without human intervention. 

Humans have the ability to learn through experience. Machines with artificial intelligence can do the same.  

Machine learning is also the scientific study of statistical models and algorithms that machines use to perform a task efficiently without receiving explicit instructions. Instead, they rely on inferences and models. 

Emerj.com has the following definition of the term:

“Machine learning is the science of helping computers  learn and act like humans, and improve their learning over time in an autonomous manner, by providing them with data and information in the form of observations and interactions.” work in the real world.” 

Neural network – a set of algorithms  modeled after the human brain, is an example of machine learning. 

What is Artificial Intelligence and Machine Learning?

AI stands for artificial intelligence. AI includes software technologies that help machines like computers and robots think like us (humans). It also makes them behave like us. 

Humans have natural intelligence. On the other hand, “smart” machines are equipped with artificial intelligence.  Artificial intelligence is rapidly becoming more pervasive in our homes, businesses, and manufacturing processes.  

We often refer to the ability to learn without human assistance when describing AI. We refer to machine learning, which is part of AI.  

Machine and human learning – simple example 

If we see a trend, we can sometimes use our intelligence to draw conclusions. For example, see this test: 

2 – 20 

5 – 50 

10 – 100 

100 – 1000 

500 – ?  After seeing a pattern, i.e. every time we multiply the first number by 10, we get the answer as “5000”. With machine learning, we are trying to teach the machine this kind of behavior. In other words,  learn from experience.  

According to Becoming Human – Artificial Intelligence Magazine:

“Machine learning algorithms use computational methods to ‘learn’ information directly from data, without relying on a predefined equation as a model.” 

“Algorithms improve their performance adaptively as the number of samples available for training increases.” 

A Term Process 

According to American multinational IBM, machine learning allows us to learn continually from data. This helps us, for example, to predict the future.

Powerful sets of models and algorithms are  used in almost every industry. They improve processes and help us better understand patterns and anomalies in the data.  

However, it is not a solitary job. This is a team process that requires business analysts, data scientists, and data engineers. We also need business leaders. They all work together.  IBM says: 

“The power of machine learning requires  collaboration, so the focus is on solving business problems.”

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