Explore Machine Learning Models with Explainable AI: Challenge Lab

FIRST MODEL ----------------------------------------------------------------------------------------------------------

model = Sequential()
model.add(layers.Dense(200, input_shape=(input_size,), activation='relu'))
model.add(layers.Dense(50, activation='relu'))
model.add(layers.Dense(20, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
model.fit(train_data, train_labels, epochs=10, batch_size=2048, validation_split=0.1)



SECOND MODEL ----------------------------------------------------------------------------------------------------------

limited_model = Sequential()
limited_model.add(layers.Dense(200, input_shape=(input_size,), activation='relu'))
limited_model.add(layers.Dense(50, activation='relu'))
limited_model.add(layers.Dense(20, activation='relu'))
limited_model.add(layers.Dense(1, activation='sigmoid'))
limited_model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
limited_model.fit(limited_train_data, limited_train_labels, epochs=10, batch_size=2048, validation_split=0.1)



LAST CODE  ---------------------------------------------------------------------------------------------------------------

config_builder = (WitConfigBuilder(
    examples_for_wit[:num_datapoints],feature_names=column_names)
    .set_custom_predict_fn(limited_custom_predict)
    .set_target_feature('loan_granted')
    .set_label_vocab(['denied', 'accepted'])
    .set_compare_custom_predict_fn(custom_predict)
    .set_model_name('limited')
    .set_compare_model_name('complete'))
WitWidget(config_builder, height=800)

FOLLOW MY INSTUCTIONS WHILE FOLLOWING FROM THIS FILE!
Thank you!
:)