title: How to improve CNN accuracy further with this code at [github][2]?
body: <p>I am playing with the code listed here by Daniel Persson on <a href="https://www.youtube.com/watch?v=bqeUmLCgsVw" rel="nofollow noreferrer">Youtube</a>. His code at <a href="https://github.com/kalaspuffar/tensorflow-data" rel="nofollow noreferrer">github</a>.</p>
  
  <p>I am playing with his code for my classification project and I got accuracy of about 88% (I am using a GPU). BUt I got about 93% with InceptionV3 and RasNEt50 transfer learning. I am new to ML and I managed to setup basic training models using Keras. I am using 3 classes (120x120 pxl RGB images). In the above code, I could not find how to change cross-entropy to categorial-cross-entropy. </p>
  
  <p>What are the other methods to improve the accuracy level? I feel the output should be better since images differences are trivial to humans.</p>
  
  <ol>
  <li>Will this improve increasing hidden layers ?</li>
  <li>A number of nodes in existing layers ?</li>
  </ol>
  
  <p>Also I would like to know how I could use sklearn kit to plot confusion matrix here. </p>
  
  <p>Thank you in advance.</p>