List of top Artificial Intelligence Questions asked in WBBSE XII

Explain the purpose of the Train-Test Split technique in evaluating model performance.
Define Computer Vision and list its primary pipeline stages (Acquisition, Preprocessing, Feature Extraction).
What is a Confusion Matrix, and how do you calculate Accuracy, Precision, and Recall from it?
Explain the Turing Test and its significance in measuring machine intelligence.
Discuss the major ethical issues in AI, such as Bias, Privacy, and Accountability.
Explain the biological motivation behind Artificial Neural Networks (ANN).
Differentiate between Supervised and Unsupervised Learning with real-world examples.
Explain the concept of Linear Regression and the role of the Mean Squared Error (MSE) loss function.
What is the Gradient Descent algorithm and how does it help in model optimization?
Explain the 10 stages of the Foundational Methodology for Data Science.
Why is the "Business Understanding" stage considered the most critical phase of an AI project?
Describe the five stages of Design Thinking: Empathize, Define, Ideate, Prototype, and Test.
Define the 5 Vs of Big Data: Volume, Velocity, Variety, Veracity, and Value.