Machine learning

Machine learning Machine learning (ML) is a field of study that involves the development of algorithms and statistical models which enable computing systems to develop skills in specific areas, by using data-based training and evaluation. Commonly this leads to Artificial Intelligence (AI) cognitive services, such as computer vision and image recognition.

Machine learning model

A model, under a more general perspective, is the mathematical representation of a real-life system, e.g. a simulator or emulator of an airplane uses airplane flight navigation models and turbo jet engine models. A machine learning (ML) model is a mathematical representation of data applied to an algorithm.


MAE in statistics and Machine Learning (ML) stands for the Mean Absolute Error. MAE is the average of the sum of the differences between the actual and predicted values in a dataset. In other words the MAE is the calculation of the the average of the residuals. MAE is expressed by the following mathematical formula. ... Read more


Matplotlib is a Python programming language library which is used in applications which need to create and process visualizations. Visualizations can be static, animated or interactive. The major visualization types which can be managed by Matplotlib are: Pairwise data Statistical distributions Gridded data 3D and volumetric data The official Matplotlib documentation can be found at: ... Read more


Multi-platform App UI (MAUI) .NET Multi-platform App UI (.NET MAUI) is a cross-platform framework for creating native mobile and desktop apps with C# and XAML.


MFA Multi-factor authentication (MFA) is the process of authenticating an identity into a computing system, application or service by providing at least two of the following authentication factors: The following list provides the most common MFA factor implemented today by security companies:


MSE in Machine Learning (ML) stands for Mean Squared Error and is an error calculation formula. MSE calculates the average value of the square power of the sum of differences between the original and predicted values in a dataset. It is similar to MAE, in that MSE is a calculation for the variance of residuals, ... Read more