AI Project Cycle

Correct answer: A. Teaching a machine to learn patterns from examples and data

Training is the stage in which a model is given examples and adjusts its internal parameters to learn useful patterns. After training, the model can perform inference on new data. Therefore option A describes training, while option B describes later prediction or inference, not the learning stage itself.

Correct answer: A. The solution may be developed for the wrong problem

A clear purpose is needed to define the problem, select relevant data, choose suitable success measures, and evaluate the result. Without it, a team may build a technically impressive system that does not solve the real need. Therefore, option A is correct; unclear goals do not automatically improve accuracy or remove bias.

Correct answer: A. उपयुक्त समाधान के लिए समस्या, हितधारकों और अपेक्षित परिणाम को स्पष्ट करना

Problem identification defines what needs to be solved, who is affected or involved, what constraints exist, and what successful results should look like. This foundation guides data collection, model selection, and evaluation. Choosing a model before understanding the need can solve the wrong problem, while deleting data or changing results without a goal has no sound project purpose.