I am building SVM model for MNIST Digit recognition in Amazon Sagemaker and I am getting below error.

MemoryError: Unable to allocate 201. MiB for an array with shape (33600, 784) and data type float64

Below is my code:-

# creating a KFold object with 5 splits 
folds = KFold(n_splits = 5, shuffle = True, random_state = 101)

# specify range of hyperparameters
# Set the parameters by cross-validation
hyper_params = [ {'gamma': [1e-1, 1e-2, 1e-3, 1e-4],
                  'C': [1e-3, 1e-2, 1e-1, 1, 10, 100]}]


# specify modelb
model = SVC(kernel="rbf")

# set up GridSearchCV()
model_cv = GridSearchCV(estimator = model, 
                     param_grid = hyper_params, 
                     scoring= 'accuracy', 
                     cv = folds, 
                     verbose = 1,
                     return_train_score=True)      

# fit the model
model_cv.fit(normalized_X_train, y_train)  

print("The best parameters are %s with a score of %0.2f"
    % (model_cv.best_params_, model_cv.best_score_))