Howtoperformquant machinelearning

There are some concepts in math and linear algebra that are important to understand quantum machine learning. Knowing some basic Python is also very useful if you want to program an algorithm using some of the most popular frameworks available.

Machine learning and quantum computing are two major topics which needs to be understood in order to perform quantum machine learning and quantum computing (Cerezo et al., 2022) .

The goal of machine learning is to utilise computers to find trends in data and extrapolate those patterns and trends to data that has never been seen before. It entails creating a computer algorithm that, without being explicitly designed, may increase its performance on a job (learn).

Quantum machine learning has many ideas that are connected to optimization. Identifying the sources that will result in the best feasible output for a particular problem is the goal of optimization problems, which can be found in a wide range of academic disciplines.

Once a cost function has been established, an optimization approach must be chosen. Generally speaking, you reduce your objective functions by taking a set of actions that ultimately result in the lowest cost (Schuld et al., 2015) .