What is Gradient? Loss Function? Model Parameters? Gradient Descent?

Gradient Descent: Optimization algorithm; minimizes errors between predicted and actual results; updates parameters by moving against the gradient Loss Function: aim is to minimize this function, closer to zero; measures how bad the prediction is in comparison to the actual true value; various methods are used; one is Mean Squared Error (MSE) Gradient: Slope; direction ... Read More

Terms in Quantum Computing

Quantum Circuit: Observables: In quantum physics, physical properties/quantity that can be measured. eg. system’s energy, alignment of spins (for a system of spins)http://docs.quantum.ibm.com/guides/specify-observables-paulihttps://en.wikipedia.org/wiki/Observablehttps://www.quantiki.org/wiki/observables-and-measurementshttps://jonathan-hui.medium.com/qc-observable-8a44d10c3f7a EigenValues and EigenVectors: https://www.youtube.com/watch?v=PFDu9oVAE-g&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_abLinear Algebra – https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Quantum State: Expectation Values: Expected value of the meaurement or result of an experiment; average of all possible results. https://www.youtube.com/watch?v=8VgBPEcZ_X0https://phys.libretexts.org/Bookshelves/Quantum_Mechanics/Essential_Graduate_Physics_-Quantum_Mechanics(Likharev)/04%3A_Bra-ket_Formalism/4.05%3A_Observables-_Expectation_Values_and_Uncertainties Measuring expectation Values: Unitary Gate:
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