TensorFlow and Keras -1
Q1. Binary classification In order to perform binary classification on a dataset (class 0 and 1 ) using a neural network, which of the options is correct regarding the outcomes of code snippets a and b ? Here the labels of observation are in the form : [0, 0, 1...]. Common model: import tensorflow from keras.models import Sequential from keras.layers import Dense from tensorflow.keras.optimizers import SGD model = Sequential() model.add(Dense(50, input_dim=2, activation='relu', kernel_initializer='he_uniform')) opt = SGD(learning_rate=0.01) Code snippet a: model.add(Dense(1, activation='sigmoid')) model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy']) Code snippet b: mode.add(Dense(1, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=['accuracy']) The term " Required results " in the options means that the accur
