This is the tutorial presented to the contest Teach Me QISKit 2019 / 20.
In this tutorial, we will learn a little bit about Quantum Machine Learning and how to apply it using the IBMQ-experience platform. We will solve toy-problems related to classification in Supervised Machine Learning using a few qubits. We will show that one qubit has got enough computational power for classifying classical data. The critical idea that is the core of this method is re-uploading. Re-uploading classical data several times into a single-qubit quantum circuit via unitary operations allows us to classify any kind of data into any number of classes. This idea can also be extended to more qubits for improving the performance of the classifier.