Can someone help me build an MLP deep neural network using Keras for the MNIST dataset? (Python). Thank you.

Build an MLP deep neural network to classify MNIST dataset to get to the target goal of 98% accuracy or higher To re-iterate, build an MLP deep neural network, fine tune your solution to get to the target accuracy of 98% The dataset can be loaded using keras.datasets.mnist.load_data(). Design an MLP with at least two different sizes (10 points) Use concepts that we covered in the class o Adding checkpoints (5 points) o Early stopping (5 points) Save all the tries that you make. Save the code, settings, the results, and plot of loss. Also submit them along side of the final model which hits the target. Clearly mark the final model and its setting that reached the target performance of higher than 98%. (5 points) Build an MLP deep neural network to classify MNIST dataset to get to the target goal of 98% accuracy or higher To re-iterate, build an MLP deep neural network, fine tune your solution to get to the target accuracy of 98% The dataset can be loaded using keras.datasets.mnist.load_data(). Design an MLP with at least two different sizes (10 points) Use concepts that we covered in the class o Adding checkpoints (5 points) o Early stopping (5 points) Save all the tries that you make. Save the code, settings, the results, and plot of loss. Also submit them along side of the final model which hits the target. Clearly mark the final model and its setting that reached the target performance of higher than 98%. (5 points)