In the attached Jupyter notebook, I have presented a code to implement a Quantum Machine Learning (QML) algorithm for a classification task. In the algorithm, we pass the training set through a (Quantum Neural Network) QNN, which is a parameterized quantum circuit [https://iopscience.iop.org/article/10.1088/2058-9565/ab4eb5]. Our QNN is trained through a gradient descent algorithm, which is executed through the parameter sift rule [https://arxiv.org/abs/1803.00745 and https://arxiv.org/abs/1811.11184].
To be precise, it is a classical simulation of the quantum algorithm that can be run on a normal laptop. One can easily turn it into an algorithm that can be run on an actual quantum computer.