In python, make a machine learning model to predict a 5x5 minesweeper game. You can’t make it random or make it predict 2 same results in a row if a new game is started. You have data for the past 30 games [5, 12, 13, 4, 17, 19, 4, 18, 21, 1, 6, 11, 7, 15, 22, 14, 18, 19, 1, 19, 20, 9, 16, 17, 1, 19, 20, 6, 14, 24, 15, 20, 22, 7, 18, 21, 4, 16, 23, 5, 11, 19, 5, 6, 23, 6, 12, 13, 0, 5, 15, 1, 5, 22, 0, 2, 23, 5, 10, 13, 5, 12, 17, 1, 7, 22, 7, 11, 18, 7, 8, 9, 17, 21, 24, 13, 14, 16, 2, 3, 11, 7, 17, 18, 7, 14, 21, 2, 5, 9] and you need to predict x safe spots that are giving by the user and x possible bomb locations that amount is the giving mines amount.The data lenght changes by the selected mines. It's mines x 30, = all mine past data. So 3 mines becomes 90 past mines. You need to use the list raw and it needs to get the same data if the mine locations are not changed. It also needs to the accuracy