What is the difference between the Fractional Knapsack problem and the 0-1 Knapsack problem?
SIKSHAPATH Latest Questions
A drug tester claims that a drug cures a rare skin disease 69% of the time. To verify this claim, the drug is tested on 100 patients. If at least 63 patients are cured, the claim will be accepted. Find the ...
After initializing your AutoEncoder you are all set to train it. Which of the following pieces of code will you use? def autoencoder_training (X_train, Y_train, epochs): history autoencoder.fit (# YOUR CODE HERE) return history Options: i. autoencoder.fit(X_train, ...
Consider the following code for a simple AutoEncoder, what is model_1 outputting ? inputs = tf.keras.layers.Input(shape=(784,)) def simple_autoencoder(): encoder = tf.keras.layers.Dense(units=32, activation=’relu’)(inputs) decoder = tf.keras.layers.Dense(units=784, activation=’sigmoid’)(encoder) return encoder, decoder output_1, output_2 = simple_autoencoder() model_1 = tf.keras.Model(inputs=inputs, outputs=output_1) model_2 = tf.keras.Model(inputs=inputs, outputs=output_2) options: Displaying the reconstruction of the original input ...
Consider the values given in the image below and calculate the content loss value. Generated image: 5 2 1 7 and content image : 3 5 5 4
Consider the following code snippet. How will you include Total Loss Variation in it? Use TensorFlow as tf. (Answer in the format, x + y(z), considering python’s spacing convention) def calculate_gradients(image, content_targets, style_targets, style_weight, content_weight,with_regularization=True): total_variation_weight = 30 with tf.GradientTape() as tape: if with_regularization: loss += ...