This new code walkthrough by me on Keras.io 4 talks about gradient centralization, a simple trick that can markedly speed up model convergence which is implemented in Keras in literally 10 lines of code. This can both speed up the training process and improve the final generalization performance of DNNs.
Further, this code example also shows the improvements on using Gradient Centralization while training on @Laurence_Moroney 's Horses v Humans dataset.

  
      

      keras.io
  

  
    

Keras documentation: Gradient Centralization for Better Training Performance 18



  

  
    
    
  

  


This was also my first time contributing to Keras examples  and many thanks to @fchollet and @Sayak_Paul for helping all along!