Overview of Quantum Machine Learning
It can be understood as integration between Machine Learning and Quantum computing. The main goal of introducing to provide the power of Quantum processing to the different computations and calculations involved in Machine Learning.
Quantum Machine Learning Features
- It provides exponentially high memory capacity.
- It can provide relatively good performance with less number of hidden neurons.
- It offers faster learning.
- It process with a processing speed of 1010 bits/s.
Implementing Quantum Machine Learning
It can be used to implement different machine learning techniques such as KNN, Support Vector Machine now, even with the introduction of Quantum Neural Networks. It can be used for handling deep learning tasks also.
Xenonstack Glossary
