What does it mean when an Actual vs Predicted plot is like this assuming you are using the best model?
It's not said taht you are doing something wrong, some datasets don't contain highly predictable data. However in this case it seems there is a pattern in your data that your models is not capturing. I have a couple of questions about it:


Is there a big difference between train and test performances? If so, you must use some regularization techniques, such as dropout, in order to reduce overfitting.
What is the architecture of your Neural Network? And did you try different ones?