AI accelerator

AI accelerator An AI accelerator is a specialized hardware component which is mainly utilized for artificial intelligence tasks. It can perform AI computations in a more efficient manner than conventional computer processors (CPU), hence AI accelerators are also known as Neural Processing Units (NPU). By using algorithms for parallelism, AI accelerators can enchance performance of ... Read more

AI hardware

Artificial Intelligence (AI) relates to computer hardware in multiple ways, as follows: AI platforms are being used to optimize the design and manufacturing of new compute hardware systems. Special computer hardware processor units, referred to as AI accelerators or Neural Processing Units (NPU) are being developed to enhance the performance of AI applications and machine ... Read more


An algorithm is a series of instructions, either in the form of pseudo-code or in a computer programming language, which aim at solving a problem or at performing some sort of computation. Algorithms are therefore strongly connected to various fields of mathematics and physics, such as probability and statics, calculus and linear algebra. Algorithms apply ... Read more


ANN stands for artificial neural network. It is an electronic neural network which simulates the operations and features of human brain neural networks.

artificial intelligence

Artificial intelligence (AI) means developing intelligence in computing systems and robots. Artificial intelligence emulates human brain intelligence and is capable of executing tasks which require cognitive ability. The most common cognitive services which can be implemented in AI are the following: Language, including Natural Language Processing (NLP) and Natural Language Understanding (NLU) Computer vision, including ... Read more


Application-Specific Integrated Circuits (ASICs) are custom-built integrated circuit (IC) electronic systems, which are designed to optimize AI and ML workloads. ASICs have a large application spectrum, including for example video and voice codecs. In contrast to ASICs which are application specific, there are various general purpose Integrated Circuit systems, such as FPGAs.


AUC stands for Area Under the Curve. This refers to the two-dimensional area which is defined by a mathematical plot curve, the x-axis and two boundary points.


In machine learning (ML), bias is a concept which is related to errors in the model's predictions, as a results of multiple assumptions and simplifications in the machine learning algorithm. Due to these assumptions, the ML model becomes easy to explain (explainability) but it often misses to capture the complexity inside the training and testing ... Read more

coefficient of determination

The coefficient of determination (also depicted as R^2) is a calculation of the proportion of the variance in the dependent variable (noted as y) which is explained by a linear regression model. The value of the coefficient of determination can be in the 0..1 range. The coefficient of determination can be calculated by using the ... Read more

cross validation

In machine learning (ML), cross validation is a method in which the data scientists perform an evaluation of an ML model's performance on unlabelled data, i.e. data which the ML model has not seen before. In the method of cross validation, the data which is available in the dataset is split into multiple subsets. One ... Read more


ETL stands for extract, transform, and load. It refers to a data science and machine learning procedure, in which ML model data is being collected (extracted) from data sources, then data is transformed and finally loaded into an ML model.

good fit

A "good fit" or "best fit" or "sweet spot" is when a machine learning (ML) model can predict values for a system with the minimum error, ideally that error being zero. In this case, the ML model is said to have a good fit on the data. The good fit sits between the underfitting and ... Read more


Graphics Processing Units (GPUs) have been traditionally used in computing systems for image processing (graphics cards). Their usage has largely been expanded to AI and ML tasks and are largely used for optimizing performance of neural networks.


In machine learning, holdout validation is a data sampling method in which the dataset is split into two: the training dataset and the test. The split is equal, i.e. training is performed on the 50% of the dataset and testing is performed on the remaining 50% of the dataset. Holdout validation is not recommended in ... Read more

k-fold cross validation

In machine learning, k-fold cross validation is a type of cross validation in which the dataset is split into k subsets and the validation process is repeated k times. Each time k-1 subsets are used for training the ML model, while one (1) subset is used for testing/validation. The final validation generalization capability/performance of the ... Read more


Keras is one of the most recognized deep learning APIs. Keras has been developed in the Python programming language and can be executed on top of JAX, TensorFlow, or PyTorch. More details about Keras can be found in its official website at:

linear regression

Linear regression is a statistical modeling technique. It utilizes a dependent variable, which can be discrete or continuous number and one independent variable. Linear regression models are simple to train by using machine learning. In many cases are the first type of machine learning models to try to train when using a new data set. ... Read more


In machine learning, LOOCV stands for leave-one-out cross validation. Assuming that the dataset of an ML project comprises n examples (rows), we split the dataset into n subsets and perform n iterations of training/testing. In each iteration, n-1 examples are used as training data and only 1 example is used the testing subset. This process ... Read more

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.