Arcsine transformation : The arcsine transformation is a mathematical operation that is used to transform data from a range of 0 to 1 into a range of -1 to 1. This transformation is commonly used in statistics to normalize data and to make it easier to analyze and compare. For example, suppose that we have […]

Annuity Rate : Annuity rate is the rate of interest earned on an annuity, which is a financial product that provides regular payments over a set period of time. It is typically used to provide a steady stream of income for individuals during retirement, or to help save for future expenses such as a child’s […]

Anamoly Detection : Anomaly detection is a technique used to identify unusual patterns or events in data that do not conform to expected behavior. These anomalous patterns can indicate a variety of issues, such as fraud, security breaches, or technical malfunctions. One example of anomaly detection is in the financial industry, where it is used […]

Analytical Categories : Analytical categories are frameworks or models used to organize and classify data or information in order to better understand it. These categories provide a structure for analyzing complex information and can be used in various fields such as business, sociology, and psychology. One example of an analytical category is the five-factor model […]

Anaconda : Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. It is the most popular Python data science platform, and is used by over 7 million users […]

Akaike information criterion : Akaike information criterion, also known as AIC, is a statistical measure used to evaluate the quality of a model by comparing the goodness of fit of the model with the number of parameters in the model. The AIC is calculated by adding the residual sum of squares (RSS) and twice the […]

Alpha : Hyperparameter alpha refers to the smoothing parameter in the additive smoothing technique, which is a method of smoothing data in natural language processing and other fields. This technique is used to smooth out the impact of a particular word or event on the overall distribution of data, by adding a small amount of […]

Age-related reference ranges : Age-related reference ranges refer to the normal values of various laboratory tests and measurements that are specific to different age groups. These ranges provide a basis for interpreting test results and determining whether they fall within the normal range for a person’s age. For example, the normal range for hemoglobin in […]

Adam Optimisation : Adam (Adaptive Moment Estimation) is an optimization algorithm for training deep learning models. It is a variant of stochastic gradient descent (SGD) that uses moving averages of the parameters to provide a running estimate of the second raw moments of the gradients; the name Adam is derived from adaptive moment estimation. Adam […]

Activation Classification : Activation classification is a method used in machine learning to determine the output of a neural network. It is a way of categorizing the various activation functions used in neural networks, and it helps to understand how the neural network processes information. There are four main types of activation functions used in […]