  Classical optimization algorithms in machine learning often take a long time
to compute when applied to a multi-dimensional problem and require a huge
amount of CPU and GPU resource. Quantum parallelism has a potential to speed up
machine learning algorithms. We describe a generic mathematical model to
leverage quantum parallelism to speed-up machine learning algorithms. We also
apply quantum machine learning and quantum parallelism applied to a
$3$-dimensional image that vary with time.
