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@qml.qnode(dev) def circuit(weights, x): qml.AngleEmbedding(x, wires=[0,1]) qml.BasicEntanglerLayers(weights, wires=[0,1]) return qml.expval(qml.PauliZ(0)) weights = np.random.random((2, 2)) print(circuit(weights, [0.5, 0.2]))

Run this in any free cloud notebook (Colab, Deepnote, or IBM Cloud Pak for Data) to experience QML without a local setup. You do not need a quantum computer or expensive license. Free cloud platforms provide immediate access to QML tools – perfect for learning, prototyping, and research.

Quantum Machine Learning (QML) sits at the intersection of quantum computing and classical ML. Thanks to several cloud platforms, you can experiment with QML algorithms today—completely free.

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!full! Free Cloud Based Quantum Machine Learning Software (Mobile)

@qml.qnode(dev) def circuit(weights, x): qml.AngleEmbedding(x, wires=[0,1]) qml.BasicEntanglerLayers(weights, wires=[0,1]) return qml.expval(qml.PauliZ(0)) weights = np.random.random((2, 2)) print(circuit(weights, [0.5, 0.2]))

Run this in any free cloud notebook (Colab, Deepnote, or IBM Cloud Pak for Data) to experience QML without a local setup. You do not need a quantum computer or expensive license. Free cloud platforms provide immediate access to QML tools – perfect for learning, prototyping, and research.

Quantum Machine Learning (QML) sits at the intersection of quantum computing and classical ML. Thanks to several cloud platforms, you can experiment with QML algorithms today—completely free.

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