Activation Functions

Anactivation functionin a neural network defines how the weighted sum of the input is transformed into an output from a node or nodes in a layer of the network.

https://machinelearningmastery.com/choose-an-activation-function-for-deep-learning/#:~:text=An%20activation%20function%20in%20a,a%20layer%20of%20the%20network.

An activation function is a mathematical function used in a neural network to determine the output of a neuron. Activation functions are used to transform the inputs into an output signal and can range from simple linear functions to complex non-linear functions. Activation functions are an important part of neural networks and help the network learn patterns and generalize data. Types of activation functions include sigmoid, ReLU, tanh, and softmax. Reference: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

https://griffinshare.fontbonne.edu/cgi/viewcontent.cgi?article=1008&context=ijds

Computer scientists and economists use the term 'utility' to describe how happy an agent is. Utility is a measure of satisfaction or preference, and it is used to evaluate an agent's satisfaction with a particular outcome. Utility can be used to determine the optimal decision or action for an agent to take in order to maximize its satisfaction. Reference:

[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, 'Decision Making and Planning', p.99-100. [2] APMG-International.com, 'Foundations of Artificial Intelligence' [3] EXIN.com, 'Foundations of Artificial Intelligence'

Technology Readiness Level(TRL) Technology Readiness Levels (TRL) are a method of estimating the technology maturity of Critical Technology Elements (CTE) of a program during the acquisition process.

https://acqnotes.com/acqnote/tasks/technology-readiness-level#:~:text=Technology%20Development-,Technology%20Readiness%20Level%20(TRL),program%20during%20the%20acquisition%20process.

TRL stands for Technology Readiness Level and is a measure of how close a technology is to being ready for use in a real-world environment. TRL is used to assess the progress of research and development of a technology, ranging from basic research (TRL 1) to fully operational (TRL 9). TRL is used to help determine the level of completion of a technology and its potential success in a real-world environment.

https://link.springer.com/referenceworkentry/10.1007/978-0-387-73003-5_293#:~:text=Definition,and%20combine%20them%20to%20use.

It works by selecting different subsets of the data, or different combinations of the hypothesis, and combining the results of each prediction in order to create a single, more accurate result. This is useful in situations where different hypothesis may be accurate in different parts of the data, or where a single hypothesis may not be accurate in all cases. Ensemble learning is used in a variety of applications, from computer vision to natural language processing.

Human-centric trustworthy Al must be continually assessed and monitored in order to ensure that it is behaving in a safe and ethical manner. This includes conducting regular tests and audits to ensure that the Al is functioning as intended, and is not taking any actions or decisions that could potentially harm humans or their environment. Reference: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/ai/certificate/and APMG International,https://www.apmg-international.com/qualifications/artificial-intelligence-foundation-certificate.