By classical, I mean the current Machine learning Algorithms we have, according to the current status of Machine Learning field, some we have or might have not gained the in-depth aspects which will/might influence the enhancement of these classical Machine Learning algorithms.
On the other side, quantum machine learning will solve computational complexity (like space complexity, time complexity or communication complexity), so as to achieve AI goals or objectives.
Will quantum machine learning be achieved besides the computational power that is slowly advancing?
What is the difference (any idea on a global perspective) between classical machine learning and quantum machine learning?
Note that, typically, the semantic difference between the two terms would be subtle enough to be irrelevant today, but if we are interested in the growth nor improving the ML algorithms due to Big Data generation, then the distinction would be important.