Problems with the existing approach

In this section, we will list all the points that create problems. We should try to improve them. The following are things that I feel we can improve upon:

  • If you find out that class sampling is not proper in your case, then you can adopt the sampling methods
  • We can add more layers to our neural network

We can try different gradient descent techniques.

In this approach, training takes a lot of time that means training is computationally expensive. When we trained the model, we used GPUs even though GPU training takes a long time. We can use multiple GPUs, but that is expensive, and a cloud instance with multiple GPUs is not affordable. So, if we can use transfer learning in this application, or use the pre-trained ...

Get Machine Learning Solutions now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.