Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 116 discussion

Best for training a model with a labeled dataset, like the company's labeled images.

A: Supervised learning Explanation: Supervised learning is the appropriate method when a dataset of labeled examples is available, as it involves training a model using input-output pairs. In this case, the labeled images of animals (input) and their corresponding categories (output) make supervised learning the ideal approach. The model learns from these examples to classify new, unseen images into the correct categories. Why not the other options? B: Unsupervised learning: Unsupervised learning does not use labeled data and is typically used for clustering or pattern discovery. It is not suitable for this classification task, which requires labeled data.

A. Supervised learning Explanation: Since the company has a large dataset of labeled images, supervised learning is the appropriate choice. In supervised learning, a model is trained on a labeled dataset, where the input data (images) is paired with corresponding labels (the types of animals). This approach allows the model to learn from the labeled data and make predictions on new, unseen data.