Consider the following gathered dataset from a manufacturing process where we want to predict if a material is safe given its Volume, Density, and Shape. The "Is Safe?" column indicates it is safe (1) or not safe (0). Your supervisor has already split the data into training and validation sets. Validation Data 1.1 What kind of supervised learning task is this? 1.2 Which columns are the input features of this supervised learning task? 1.3 Which columns are the output labels of this supervised learning task? 1.4 Which of the input features are most likely continuous? 1.5 Which of the input features are most likely discrete (finite set of values)? 1.6 Based on the training set, how would you use one-hot-encoding on Shape; show the value to code mapping. Apply this to the Validation data's Shape column. 1.7 Now suppose that Shape can only have four possible values { Sphere, Cube, Cylinder, Cone\} . How would you use one-hot-encoding on Shape; show the value to code mapping. Apply this to the Validation data's Shape column