title: Problem with numpy the dot product does not work
body: <p>I am currently learning linear algebra and I am trying to try out what I learn in code. I am using numpy in python. </p>
  
  <p>The problem is that as you know any matrix multiplied with its inverse it will give us the the identity matrix. </p>
  
  <p>but here it does not happen. </p>
  
  <pre><code>B= np.array([[3.0, 0.0, 2.0], [2.0, 0.0, -2.0], [0.0, 1.0, 1.0]])
  Binv = np.linalg.inv(B)
  Bbits= np.dot(B,Binv)
  </code></pre>
  
  <p>I have tried it manually. It gets the inverse correctly but the dot product is not. 
  See the output of Bbits</p>
  
  <pre><code>[[ 1.00000000e+00  0.00000000e+00 -5.55111512e-17]
   [ 0.00000000e+00  1.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  1.00000000e+00]]
  </code></pre>