The difference between Machine Learning and Deep Learning
The early thinkers of A.I wished to create exact artificial replica of the brain of a typically intelligent human being. However, the neural pathways of a typical human brain are so complex, with its neural networks so diverse, that developing a system similar to it seemed a practical impossibility. This ambitious goal of early artificial intelligence developers has been termed as 'general AI' whereas what we work today with is called narrow AI- artificial intelligence smart enough only to perform specific tasks demanding a specific set of instructions.
Machine learning instead is a notch more complex version of early artificial intelligence, where a system recognizes instructions from an earlier set of codes by scanning years of data to work on its own, essentially by 'learning' what had been previously taught to it via manually written coded instructions.
Finally, ' deep learning' is a more sophisticated version of machine learning which involves the use of big data and parallel processors to attain near-human intelligence and problem solving abilities. Understandably, with computer vision and machine learning working hand in hand to analyze big data sets faster , the field of medical diagnosis is gearing up for a revamp. It is now necessary to look at the employment of predictive data tools from the point of view of healthcare diagnostics