Quantum machine learning uses qubits and quantum operations to improve computational speed and data storage done by algorithms in a program. Specialized quantum systems are used to compute vast quantities of data executed on the quantum computer – i.e. quantum-enhanced machines, quantum machines are the integration of quantum algorithms within machines.
Quantum algorithms can be used to analyze quantum states instead of classical data. The term “quantum machine learning” is also associated with classical machines applied to quantum data generated from quantum experiments.
Quantum machine learning also extends to a branch of research that explores methodological and structural similarities between physical systems and learning systems. Some mathematical and numerical techniques from quantum physics are applicable to classical deep learning and vice versa.
Source:
[1] Wikipedia Contributors. “Quantum Machine Learning.” Wikipedia, Wikimedia Foundation, 4 Jan. 2021, en.wikipedia.org/wiki/Quantum_machine_learning. Accessed 8 Jan. 2021.
[2] ziggy2012. “Urban City Skyline – Free Image on Pixabay.” Pixabay.com, 14 May 2016, pixabay.com/illustrations/urban-city-skyline-sketch-1389838/. Accessed 8 Jan. 2021.