Train a neural model

Objective: You are required to train a neural net model for the handwritten data set. Python script will be used to evaluate each code. Only use python version 3 (not 2) for coding. Input to file: Your code should accept command line parameters. It should take one image file name as input, e.g. python3 [login to view URL] [login to view URL] Input image file will have fixed 20x20 size in grayscale. In the given dataset images are saved in the form of rows of 400 length. These rows can be converted into 20x20 grayscale images by using following python code. (You may import packages form numpy and matplotlib) [login to view URL](filename, [login to view URL](data).reshape(20,20).T,cmap="gray") In the example above data is the row data of X. for example X[0], X[3455] so on, “filename” is the name of the image file. It can be any name like “[login to view URL]”, “[login to view URL]” so on. Output of file: Output of your code should be the predicted digit. Only digit in one line must be written as output. Testing your code: Script will evaluate each code. I shall provide the input image (unseen) (size 20x20, gray scale) to your code and will give +1 or 0 reward for each right and wrong prediction respectively. Same test data set will be provided to each script.