A self-driving car company has millions of images labeled with either "pedestrian" or "no pedestrian". They want the car to automatically detect pedestrians. Which type of learning and algorithm would be optimal for this task?
- Supervised Learning with Convolutional Neural Networks
- Unsupervised Learning with Apriori Algorithm
- Reinforcement Learning with Monte Carlo Methods
- Semi-Supervised Learning with DBSCAN
Supervised Learning with Convolutional Neural Networks (CNNs) is the optimal choice for image classification tasks like pedestrian detection. CNNs are designed for such tasks, while the other options are not suitable for image classification. Apriori is used for association rule mining, reinforcement learning for decision-making, and DBSCAN for clustering.
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