Q1) Answer by True or False and correct if false: 1. Machine Learning is the field of study that gives computers the ability to learn by explicitly programming the problem. 2. Supervised learning is training a data which is already tagged with correct answers. 3. Features are the number of attributes and target that represent the problem. 4. Generalization is to make a prediction on seen data. 5. In Linear Regression, he following equation is called the loss function: J(0)-(he(20)-2 6. The model performance on training data is more important than the testing data.

Q1) Answer by True or False and correct if false: 1. Machine Learning is the field of study that gives computers the ability to learn by explicitly programming the problem. 2. Supervised learning is training a data which is already tagged with correct answers. 3. Features are the number of attributes and target that represent the problem. 4. Generalization is to make a prediction on seen data. 5. In Linear Regression, he following equation is called the loss function: J(0)-(he(20)-2 6. The model performance on training data is more important than the testing data.