QUESTION :

What is the difference between a learning algorithm and a hypothesis? Write down one possible hypothesis for a linear regression problem in which the input dimension is d=3

ANSWER :

"A learning algorithm is a procedure or set of instructions used to find an approximate solution to a problem, such as finding a hypothesis that fits a given dataset. A hypothesis, on the other hand, is a statement or function that describes the relationship between inputs and outputs in a problem.

One possible hypothesis for a linear regression problem with input dimension d=3 is a linear function of the form h(x) = w1(x1) + w2(x2) + w3(x3) + b where w1, w2, w3 and b are parameters to be learned from the data.

IDENTIFY WHETHER THE ANSWER TO THE ABOVE QUESTION IS CORRECT OR NOT AND EXPLAIN WHY?