How do parameterized quantum gates and entangling operations, such as the CNOT gate, contribute to designing a quantum circuit capable of learning the XOR function?
Tuesday, 11 June 2024
by EITCA Academy
The XOR problem, or exclusive OR problem, is a classic problem in machine learning and neural networks which involves learning the XOR function. The XOR function outputs true only when the inputs differ. Traditional linear models struggle with the XOR problem due to its non-linearity. Quantum computing, particularly quantum machine learning, offers promising approaches to
Explain the role of parameterized quantum gates (e.g., RX, RY, RZ gates) in constructing a quantum model for the XOR problem using TensorFlow Quantum.
Tuesday, 11 June 2024
by EITCA Academy
The XOR (exclusive OR) problem is a classic problem in the field of machine learning and artificial intelligence, where the goal is to correctly classify binary inputs (0, 1) into their corresponding XOR outputs. The XOR function outputs true (or 1) only when the inputs differ (i.e., one is true and the other is false).