Splitting data into training and test data sets is an important step in the machine learning data preparation process. This process involves splitting the data into subsets, usually in a 70:30 ratio, to create a training set and a test set. The training set is used to train the machine learning model, while the test set is used to evaluate the model's performance. This process allows for the model to be tested and evaluated on data that it has not seen before, in order to ensure that it is accurate and able to generalize to new data. Reference: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

Least Squares Regression is a statistical technique used for fitting a curve to a set of data. It involves minimizing the sum of the squares of the differences between the observed data and the fitted curve. This is done by finding the line of best fit, which is the line that minimizes the sum of the squared residuals. The line of best fit is determined by finding the parameters that give the minimum sum of the squared residuals. This technique is often used in data science and machine learning to create models that can be used to make predictions. Reference: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

https://research.com/careers/what-is-the-fourth-industrial-revolution

Artificial Intelligence (AI) is playing a major role in the rapid development of the Fourth Industrial Revolution. AI technologies are enabling the automation of many processes that were previously carried out by humans or machines, which has greatly increased the speed, efficiency, and accuracy of these processes. Automation is one of the main contributions of AI to the Fourth Industrial Revolution, as it has greatly increased the productivity of businesses and industries, while reducing the cost of production and improving the quality of products. Reference:https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/https://www.apmg-international.com/en-gb/courses/fourth-industrial-revolution/fourth-industrial-revolution-foundation-and-certification/

The European Union's Ethical Guidelines for Trustworthy AI use a human-centric value system to demonstrate that Artificial Intelligence (AI) is trustworthy. This value system is based on human rights, autonomy, safety, privacy, transparency, accountability and fairness. The guidelines also state that AI should be designed, developed and used in a manner that respects these values. Reference:

https://ec.europa.eu/digital-single-market/en/news/ethical-guidelines-trustworthy-ai

BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), A.I & Ethics, Chapter 5.

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.