Kaggle competition: Natural Language Processing with Disaster Tweets
<prepare_x_and_y><EOS> 
import pandas as pd
<SOS> metric: meanfscore Kaggle data source: natural-language-processing-with-disaster-tweets<choose_model_class>
import pandas as pd
datagener = ImageDataGenerator(
 rotation_range=15,
zoom_range=0.1,
width_shift_range=0.1,
height_shift_range=0.1,
)<define_variables>
test_df = pd.read_csv('/kaggle/input/nlp-getting-started/test.csv')
 gt_df = pd.read_csv(".. /input/disasters-on-social-media/socialmedia-disaster-tweets-DFE.csv" )
example = X_train[6].reshape(( 1, 28, 28, 1))
label = Y_train[6]<compute_train_metric>
gt_df = gt_df[['choose_one', 'text']]
gt_df['target'] =(gt_df['choose_one']=='Relevant' ).astype(int)
 gt_df['id'] = gt_df.index
gt_df
def lr_scheduler(epoch, lr):
return lr * 0.99<split>
merged_df = pd.merge(test_df, gt_df, on='id')
 merged_df
<choose_model_class><EOS> 
subm_df.to_csv('submission.csv', index=False )