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Question 1

What is the main challenge associated with the variance of Policy Gradient estimates?

Options :

A : It can lead to slow convergence and unstable learning

B : It complicates the implementation of target networks

C : It requires large experience replay buffers

D : It makes the reward signals less informative

Answer: A

Question 2

What is the key advantage of the "Thompson Sampling" method over the "Upper Confidence Bound" (UCB) method in Multi-Armed Bandits?

Options :

A : Thompson Sampling is simpler to implement

B : Thompson Sampling performs better in environments with large action spaces

C : Thompson Sampling naturally handles uncertainty in reward estimates

D : Thompson Sampling does not require parameter tuning

Answer: C

Question 3

Which Raspberry Pi model has the highest performance for computer vision tasks?

Options :

A : Raspberry Pi 2

B : Raspberry Pi 4

C : Raspberry Pi 1

D : Raspberry Pi 3

Answer: B

Question 4

In a multiclass classification problem, what does the term "class imbalance" refer to?

Options :

A : Disparity in the number of samples per feature

B : Unequal distribution of classes in the dataset

C : Inconsistent labeling of training data

D : Variability in feature values across different classes

Answer: B

Question 5

How does TensorFlow's tf.keras.layers.Layer differ from tf.keras.layers.Dense?

Options :

A : tf.keras.layers.Dense requires custom activation functions, while tf.keras.layers.Layer does not

B : tf.keras.layers.Layer can only be used for convolutional operations

C : tf.keras.layers.Layer is an abstract base class, while tf.keras.layers.Dense is a concrete layer implementation

D : tf.keras.layers.Layer performs matrix operations, while tf.keras.layers.Dense does not

Answer: C