Project 1

1. In the supervised learning , If the goal is to predict or estimate the insurance charges based on the given features (age, sex, BMI, children, smoker, and region), then it can be considered a supervised learning problem. In this case, the "charges" column would serve as the target variable or the dependent variable, while the other columns would be the independent variables or features.

In unsupervised learning , In this case we would not have a specific target variable to predict or estimate.

So the above data assumes the goal is supervised learning, but if the objective is different, such as identifying customer segments based on the features, an unsupervised learning approach like clustering algorithms (e.g., k-means, hierarchical clustering) could be used instead.

2. 165.67 (approx. 326 individuals)