Quantum Machine Learning

Quantum computing applied to machine learning — quantum algorithms, circuits, and advantage.

Quantum Computing Basics
Qubits, quantum gates, superposition, entanglement, and quantum circuits.
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Quantum Algorithms
Grover's search, Shor's algorithm, VQE, and QAOA for ML tasks.
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Quantum Neural Networks
Parameterized quantum circuits, hybrid classical-quantum models, and QML frameworks.
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Quantum Advantage
Quantum speedups, NISQ era limitations, and benchmarking quantum ML.
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Quantum Error Correction
Fault tolerance, error-correcting codes, and reliable quantum computation.
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Quantum Kernel Methods
Quantum SVMs, quantum feature maps, and kernel-based quantum ML.
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Quantum Software & Tools
Qiskit, Cirq, PennyLane, and frameworks for quantum ML development.
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