Gradient descent always going to infinity - matlab

Question

I've tried everything and can't figure out why my gradient descent isn't working. I've looked at numerous examples and have changed the gradient descent code multiple times. When I run the program I get a response of NaN. I then printed every iteration and saw that before I got to NaN the value was going higher and higher (or lower and lower to negative infinity). I've tried different alpha values, starting betas values, and the number of iterations and every time it doesn't work. What's going on?
Here is my code:
A = load('A2-datasets/data-build-stories.mat');
X = [ones(60,1) A.data_build_stories(:,1)];
y = A.data_build_stories(:,2);
b = gradDes(X, y);
function beta = gradDes(X,y)
alpha = 0.01;
beta = [0;0];
m = length(y);
for i = 1:1000
beta = beta - (alpha/m) * (X' * (X * beta - y));
end
end
And here is data-build-stories.mat:
770 54
677 47
428 28
410 38
371 29
504 38
1136 80
695 52
551 45
550 40
568 49
504 33
560 50
512 40
448 31
538 40
410 27
409 31
504 35
777 57
496 31
386 26
530 39
360 25
355 23
1250 102
802 72
741 57
739 54
650 56
592 45
577 42
500 36
469 30
320 22
441 31
845 52
435 29
435 34
375 20
364 33
340 18
375 23
450 30
529 38
412 31
722 62
574 48
498 29
493 40
379 30
579 42
458 36
454 33
952 72
784 57
476 34
453 46
440 30
428 21

Answer 1

you are iterating through the gradient descent with a
too big alpha for your data.
try and change it:
A = load('tmp.txt');
X = [ones(60,1) A(:,1)];
y = A(:,2);
b = gradDes(X, y);
function beta = gradDes(X,y)
alpha = 0.00000001;
beta = [0;0];
m = length(y);
for i = 1:1000
beta = beta - (alpha/m) * (X' * (X * beta - y));
end
end
b =[ 0.0001 0.0719]