Use python machine learning. Compare gradient boosting trees and random forest. What are the pros and cons of these two models?

Suppose you are designing a deep learning architecture to solve an object detection problem, where there areN numbers of objects and each object has M number of images. If the resolution of each image is 227 x 227 x 3, then answer the following questions: (a) Write down the name of the layers of your deep learning architecture including parameters dimension. (b) How many convolution layers will you use in your deep learning model and why? (c) Is it a good idea to use multiple fully connected layers? Motivate your answer

What methods can be utilised to lessen the burden caused by NPT?