Could you describe the "slice and dice" technique for the multidimensional model

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

You are developing a simulation model of a service system and are trying to create an input model of the customer arrival Process, You have the following four observations of the process of interest [86, 24,9, 50] and you are considering either an exponential distributionor a uniform distribution for the model. Using the data to estimate any necessary distribution Parameters, write the steps to plot Q-Q plots for both uniform and exponential distribution.  Write the steps clearly. Thanks.

Implement a Multi-layer perceptron model and test the model using any data set of your choice. The output should include Accuracy, Error rate, Precision, and recall rate along with the confusion matrix.

Explain the concept of mutation-driven testing for machine learning models and its applications in ensuring model robustness and reliability.