overtunned

import _pickle as cPickle

cPickle.dump(train_imgids, open('filename', 'wb'))
data = cPickle.load(open('filename','rb')).tolist()

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import zipfile
directory_to_extract_to = '/content/data'
path_to_zip_file = '/content/file.zip'

with zipfile.ZipFile(path_to_zip_file, 'r') as zip_ref:
    zip_ref.extractall(directory_to_extract_to)

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def plot_confusion_matrix(cm, classes,
                          normalize=False,
                          title='Confusion matrix',
                          cmap=plt.cm.Blues):
    """
    This function prints and plots the confusion matrix.
    Normalization can be applied by setting `normalize=True`.
    """
    plt.figure(figsize = (5,5))
    plt.imshow(cm, interpolation='nearest', cmap=cmap)

overtunned

def plot_learning_curve(history):
    plt.figure(figsize=(16,8))
    plt.subplot(1,2,1)
    plt.plot(history.history['accuracy'])
    plt.plot(history.history['val_accuracy'])
    plt.title('model accuracy')
    plt.ylabel('accuracy')
    plt.xlabel('epoch')
    plt.legend(['train', 'Val'], loc='upper left')
    plt.savefig('./accuracy_curve.png')