Newton's Method for systems

I'm trying to figure out what step 3 means in the picture attached. I know it's finding the Jacobian, but I don't understand what that means in 'Matlab code.' Also, if possible, is my code correct so far? This is what I have so far:

 function [x,ERR,k] = newtonMethod(f,j,x,Nmax,tol)
 % Inputs:
 %number of equations and unknowns, x0 = initial guess, Nmax = max iterations, 
 %tol =tolerance
 % Outputs: 
 %x = solution, ERR = error estimation, k = iterations

 %Step 1
 k = 1; ERR = 1; Niter = 50; x=x0; %tol = 10e-10;

 %Step 2
 while (k < Niter)
    %Step 3 - Compute F(x), J(x)

    %Step 4 - Solve for y s.t. J(x)*y = -F(x) using y = J\-F
    y = J(x)\(-F(x));
    %Step 5 - Set x = x + y
    x = x + y;
    %ERR
    ERR = norm(y,'inf');
    %Step 6
    if (ERR < tol)
        fprintf('convergent')
        break
    end
   %Step 7
    k = k+1;
 end
 end

[James Tursa]

How are you given f? Is it a function handle? Did the instructor tell you to use numerical difference methods to approximate the Jacobian?

[Mel Hernandez]

I believe we're supposed to input what f is, the system of equations. And the instructor didn't say. I didn't know if it would be better to do it in matlab (using jacobian command) or to do it by hand then say what it is as J. I'm just trying to understand Step 3.