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Most businesses are aware of the terms artificial intelligence (AI), machine learning and deep learning. However, the terms have caused confusion among business leaders. They want to figure out which technology is relevant to the prosperity of their businesses. They want to know what will save them time and money. So a simplified discussion of the contexts is necessary.

 

What Machine Learning Means

AI is the discipline where algorithms help computers learn from the environment. Besides machine learning and deep learning, it also covers computer vision, robotics, neural language processing, and others.

Machine learning is the part of AI that uses “neural networks”. The human brain and neurons are the models for neural networks. In machine learning, humans help create these neural network models.

Deep learning is a sub-discipline of machine learning where the neural networks are created by the machines themselves. Humans don’t have to create the models.

The application of machine learning and deep learning depends on the problem. For some cases, it is faster to let humans create the model (machine learning). In other cases, it is more efficient to let the machine develop the model (deep learning).

 

Current State of Machine Learning Adoption

According to an O’Reilly machine learning study, 49 percent of businesses considered themselves explorers and 51 percent considered themselves sophisticated users or early adopters. Businesses think that a lack of skilled labor and a lack of real-time data access are big hurdles for machine learning adoption.

 

Automation and Constant Learning

Organizations are integrating machine learning into their systems. It is becoming part of the current process. Companies are using these embedded applications to make real-time decisions. For example, insurance companies are using machine learning to study their customers. They are recommending products based on what they learn. But the process doesn’t end there. Automated machine learning algorithms can continue learning as new data becomes available.

 

More Data-driven Real-time Decisions

Machine learning is changing the business analytics framework. It is helping businesses use real-time data streams to make timely decisions. Older models of business analytics cannot compete with these data-driven applications.

 

The Larger Context for Machine Learning

Business leaders are excited about machine learning because they are seeing measurable differences in their business analytics performance. They were already using run-time decision frameworks before. But machine learning capabilities are making it possible to deploy these applications at scale.