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I want to start experimenting with quantum machine learning using Qiskit library, but I have come across an issue. All tutorials I have seen so far like this one import datasets using custom packages.

In this link its from datasets import * in other one I saw from qsvm_datasets import *, but I am unable to import any of those datasets (I get ModuleNotFound error). And I dont really understand what kind of preprocessing is being done before fitting QVSM:

sample_Total, training_input, test_input, class_labels = ad_hoc_data(
    training_size=training_dataset_size, 
    test_size=testing_dataset_size, 
    n=feature_dim, gap=0.3, PLOT_DATA=True
)
datapoints, class_to_label = split_dataset_to_data_and_labels(test_input)
algo_input = ClassificationInput(training_input, test_input, datapoints[0])

My goal is to fit my own data into the classifier, so I really want to udnerstand the steps that need to be done before fitting the classifier. Is there any documentation or more detailed tutorial that I could follow?

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