Definition of Gradient Descent Gradient descent is a popular optimization algorithm used in machine learning and data science. The goal of gradient descent is to find the minimum value of a function by systematically decreasing its value in each iteration. The algorithm takes as input an initial guess for the solution, and the derivative of…
Definition of GATE GATE is an acronym for “General Architecture for Text Engineering.” GATE is an open-source software development kit for research and development of advanced natural language processing (NLP) applications. What is GATE used for? GATE (General Architecture for Text Engineering) is a software framework developed by the University of Sheffield in 2000 that…
Definition of Growth Curve Growth Curve – A growth curve is a graphical representation of the change in some quantity over time. It can show how the quantity changes over the entire range of time being studied, or it can focus on more specific intervals of time. The most common type of growth curve is…
Definition of Gradient Boosting Gradient Boosting: Gradient boosting is a machine learning technique that combines a number of weaker models to produce a stronger model. It does this by constructing a model that takes into account the predictions of the weaker models, and uses this information to make its own predictions. What is Gradient Boosting…
Definition of G-Model G-Model: The G-Model is a data science model that is used to predict future events. It can be used to predict the behavior of customers, the sales of products, or the outcome of elections. What is a G-Model used for? A G-Model is a type of supervised machine learning algorithm used to…
Definition of Gaussian Distribution Gaussian Distribution – A Gaussian or normal distribution is a type of probability distribution that is bell-shaped and symmetrical. This distribution is often used in statistics to model real-world data. What is a Gaussian Distribution used for? A Gaussian Distribution, more commonly known as a normal distribution or bell curve, is…