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NEW QUESTION 26
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)

Answer: B

Explanation:
Explanation
The development of statistics in the 1800s led to the development of the Bayes' theorem, named after Reverend Thomas Bayes. This theorem is used in probabilistic inference, which is the process of using data to calculate the likelihood of a hypothesis or outcome. The theorem is used for determining the probability of an event occurring given its prior probability, as well as its associated conditions. The Bayes' theorem is also used in a variety of fields, such as machine learning, artificial intelligence, economics, and medical research.
Sources:
* BCS Foundation Certificate In Artificial Intelligence Study Guide: https://www.bcs.org/category/18071
* APMG
International: https://www.apmg-international.com/en/qualifications/qualification-resources/bcs-foundatio
* EXIN: https://www.exin.com/en/certification/bcs-foundation-certificate-in-artificial-intelligence

NEW QUESTION 27
Narrow or weak Al can be useful to robots.
Which of the following is an example of narrow Al?

Answer: C

Explanation:
Explanation
NLP - Natural Language Processing is an example of narrow AI. It is a type of AI system that is able to understand, interpret, and generate natural language. NLP has become increasingly popular over the past few years, as it has been used to create applications such as chatbots, virtual assistants, and search engines. NLP systems are able to learn language and the context in which it is used, and they are able to understand the nuances of language and its different meanings. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

NEW QUESTION 28
Splitting data into Training and Test data sets is part of what?

Answer: C

Explanation:
Explanation
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. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

NEW QUESTION 29
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