A student is trying to predict the price of cars based on the car’s features e.g. number of owners, milage, condition, brand and age. What type of problem is this?

A lawyer is trying to predict whether a particular judge will grant bail or not for a suspect. The lawyer has a dataset detailing all the cases which the judge has presided over, where the suspects features such as age, number of prior convictions and severity of crime are detailed along with whether they were granted bail or not. Which technique from the following is best suited to the problem?

Is the following statement True or False? Gradient descent is a handy technique which allows us to use non differentiable functions/models and update them iteratively towards an optimum. If the function had been differentiable we could have simply found the exact solution to the problem by setting the derivative to 0 and rearrange to find the optimal parameters.