Gradient Descent is an optimization algorithm used to minimize the loss function in machine learning and deep learning models. It is an iterative process that helps find the optimal parameters (weights) for a given model by minimizing the loss function.
Linear regression is one of the simplest and most widely used algorithms for predictive modeling. It models the relationship between a dependent (target) variable and one or more independent (input) variables by fitting a linear equation to the observed data
SVD is a powerful matrix factorization technique widely used in various fields such as statistics, signal processing, and machine learning. It decomposes a matrix into three other matrices, revealing the intrinsic properties of the original matrix
The gradient of the 2-norm (also known as the Euclidean norm) is a fundamental concept in vector calculus and optimization.
The vector 2-norm, also known as the Euclidean norm, is a measure of the length or magnitude of a vector in Euclidean space. It is widely used in various fields such as mathematics, physics, engineering, and computer science
Fiat payment gambling refers to gambling activities where players use traditional government-issued currencies (fiat money) such as US dollars, euros, yen, etc., to place bets, purchase credits, or participate in various forms of gambling
Crypto payment gambling refers to gambling activities where players use cryptocurrencies such as Bitcoin, Ethereum, Litecoin, and others to place bets, purchase credits, or participate in various forms of gambling
Wallet integration in the context of gambling refers to the integration of digital wallets (both fiat and cryptocurrency wallets) into gambling platforms to facilitate easy and secure transactions
A determinant is a scalar value that is calculated from a square matrix and encapsulates important properties of the matrix
The transpose of a vector or matrix is an operation that flips a matrix over its diagonal, converting the rows to columns and vice versa
Matrix multiplication is a fundamental operation in linear algebra that combines two matrices to produce a third matrix. It is widely used in various fields such as computer graphics, physics, engineering, and statistics
