Kernel Methods

Solve non-linear problems. Similarity measures between two data points. Moves point to different spaces in different dimensions. eg. Support Vector Machine, K-means Clustering. Work in feature space, not in data space. Encode data into feature space. Convert non-linearity to linear model. Good Resources:

Mathematical notations and objects used in describing quantum computers.

Notes from Amplitudes – Different from classical probability since it also has direction.– Represented by Complex Number State Vectors – Vectors that describe the state of qubits Vector multiplication and addition to representing Superposition

Quantum Computing Notes

Notes from \section{Introduction}\subsection{What is Quantum Computing}\subsection{Computer} Needs instructions that should be specific and unambiguous i.e. Algorithms With a set of instructions, the computer takes input information and provides output information. \subsection{Algorithm Complexity} measure the performance of the different algorithms algorithm complexity refers to how resources used by algorithms increase with respect to the size ... Read More