1) In machine learning, DR stands for dimensionality reduction. In machine learning, dimensionality reduction is a feature engineering technique, in which a large number of features in a dataset is reduced to a smaller number of features. It is important to ensure that the remaining features are meaningful and representative for the dataset and that ... Read more
DRaaS (Disaster Recovery As A Service) is a managed service in which disaster recovery is offered as a cloud service. Disaster recovery includes business continuity (BCDR) and backup as a service (BaaS). DRaaS management server can be either an on-premise or a cloud server. There are various DRaaS providers, most of which are already providing ... Read more
Edge computing refers to placing computing devices and services at the other edge of a cloud computing environment. Edge computing refers to low form factor devices, such as IoT devices, with low processing power and streaming data via network interface cards. The Cloud has the datacenters, the Edge has the IoT devices and in-between one ... Read more
Entanglement in machine learning (ML) pipelines refers to the fact that when a change is made in one of the ML pipeline steps, then other steps are affected by the change. For example, a fundamental change in the data preparation and feature engineering phases of the ML pipeline can have a drastic effect in subsequent ... 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.
F1 score is the weighted average (harmonic mean) of precision and recall. The F1 score is calculated by the following formula: F1 score = (2 x Precision x Recall)/(Precision + Recall) The more the precision and recall metrics deviate from each other, the worse their harmonic mean (i.e. the F1 score).
Firmware Firmware is low level system software, which provides access and control to a computing device hardware and hardware abstraction layers to the computing device operating system. Depending on the complexity of a computing device, there may be devices with lower complexity, such as IoT devices and sensors, which do not need a full operating ... Read more
Fitting or training in machine learning is the process by which a model learns from input data. Fitting is another word for training an ML model. Besides the ideal best fit or good fit, a model can get overfitted when overfitting occurs or it can get underfitted when underfitting occurs.
GAN stands for generative adversarial network. It is a type of a CNN neural network architecture in which two types of CNN neural networks compete against each other. In a GAN network architecture there are typically one or more generator neural networks and one ore more discriminator neural networks. The generator network performs continuous iterations, ... Read more
GDPR stands for General Data Protection Regulation. It is a privacy-related set of regulations in the European Union (EU) which controls how personally identifiable data (PID) is stored, processed and deleted from computing systems. In GDPR the two basic roles in a system which are related to the processing of data are the GDPR controller ... Read more
Cloud computing dictionary
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.
Gradient descent is a method of minimizing the machine learning model cost function in linear regression models. In the gradient descent method, the (internal) parameters of the ML model are tuned over several training iterations by taking gradual "steps" down a slope in the function graph, aiming towards a minimum error value. In gradient descent, ... Read more
Ground truth is a term commonly used in statistics and machine learning. It signifies the correct or “true” answer to a specific problem or question. Each ML model makes predictions to values or boolean classifications about a problem. Each time the ML model's prediction or classification is compared to the ground truth, which is what ... Read more
Definition of gRPC RPC is an evolution to remote procedure call (RPC) application protocol for streaming messages between clients and servers. gRPC was originally developed by Google. It is an open source protocol and it is part of the Cloud Native Computing Foundation (CNCF) services.
Harms modeling is part of responsible AI and it is a method which can identify and mitigate risks or harms which may be caused by deploying AI solutions in production.
HCI Hyperconverged infrastructure (HCI) is a software-defined IT infrastructure which virtualizes all layers of a conventional IT infrastructure (compute, networking and storage). Under the term HCI one can classify hypervisors, software-defined networking (SDN) and software-defined storage or (SDS).
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
In machine learning, a hyperparameter is a parameter external to the ML model, which controls the learning process. A hyperparameter is not related to the internal workings of the ML model but rather indirectly affects the model's internal parameters via the ML model training (fitting) process. The usage of hyperparameter types vary depending on the ... Read more