What is the main characteristics of AI?, The ability to learn., The ability to solve problems., The ability to make decisions., All the above., What is the first known example of AI?, John Lewis Donders, First-order logic, Alan Turing's machine, What are the ethical considerations of AI?, The potential for AI to replace humans in many jobs., The potential for AI to be used for malicious purposes., The potential for AI to create new forms of crime., All the above., A company develops an AI algorithm for hiring that analyzes historical data to shortlist candidates. However, the algorithm unintentionally favors male applicants over female applicants. What ethical issue does this scenario primarily represent?, Discrimination, Privacy concerns, Data bias, Lack of transparency, A government uses facial recognition technology without clear regulations, resulting in potential misuse of citizens' personal data. What ethical principle is at risk here?, Transparency, Privacy rights, Accountability, Fairness, An AI-powered chatbot is designed to interact with users in a way that mimics human conversation. However, it does not explicitly disclose that it's a bot. What ethical concern does this raise?, Transparency, Data security, Algorithmic accountability, User consent, Machine learning is:, A way for machines to learn using large data sets., A category of techniques used in the field of artificial intelligence., The technique that netflix uses to recommend you a new series., All the above., What is the main goal of Machine Learning?, To program computers without human intervention., To enable computers to learn from data and improve performance over time., To create AI systems that can outperform humans., To develop complex algorithms for data processing., Machine learning is divided into a few categories:, Supervised Learning, Unsupervised Learning, Reinforcement Learning, All the above., In traditional computer programming, you input commands. What do you input with machine learning?, patterns, programs, rules, data, Supervised Learning involves:, Using labeled data to infer the patterns between the inputs and outputs., Using unlabeled data to infer the patterns between the inputs and outputs., Using existing data to train algorithms to establish patterns and then use that to make predictions about new data., Unsupervised Learning involves:, Using labeled data to infer the patterns between the inputs and outputs., Using unlabeled data to infer the patterns between the inputs and outputs., Using existing data to train algorithms to establish patterns and then use that to make p, Unsupervised Learning is about making predictions that we know the correct answer., True, False, A key feature of Supervised Learning is:, Training a model based on the input data., The structure-based model training., Training a model based on recurring patterns., Which picture shows Supervised Learning?, , , What is the process of feeding a Machine Learning model with data to adjust its internal parameters and improve performance?, Model Validation, Model Optimization, Model Training, Model Testing, A company's predictions of future consumer preferences based on their habits are a type of:, Supervised Learning, Unsupervised Learning, Reinforcement Learning, In Machine Learning the predictions are not always accurate and correct., True, False, A typical application of Supervised Learning is:, Record preferences on a movie platform., Image recognition, Group photos into categories., None of the above., In Supervised Learning the input data can be:, Image, Audio file, Video, All of the above., In Unsupervised Learning the goal is to:, To use the input data for prediction., Look for patterns in existing data., None of the above, Facebook recognizes your friend in a picture from an album of tagged photographs. This script is an example of ..., Unsupervised Learning, Supervised Learning, Reinforcement Learning, Netflix recommends new movies based on someone's past movie choices. This script is an example of..., Unsupervised Learning, Supervised Learning, Reinforcement Learning, Analyzing bank data for suspicious transactions and flagging the fraud transactions. This script is an example of..., Unsupervised Learning, Supervised Learning, Reinforcement Learning, To create an effective Supervised Machine Learning system you need:, Large data sets that include pairs of input and output values., Significant computing power., Algorithms capable of finding correlations in large data sets., All the above..

Artificial Intelligence & Machine Learning

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