Suppose we consider a one-step binomial tree model to price a derivative that pays in the up state and in the down state.  What is the terminal expected payoff of this derivative?

Suppose we are trying to implement an ML model to capture a highly nonlinear relationship between two variables. Which of the following options does not improve the model’s ability to capture nonlinearities?

What is the last element of x?x = np.linspace(0, 0.4, 9)

Which of the following statements is true according to the passage?

For the following floor plan, is it possible to find a route that begins in one room, passes through each doorway exactly once, and ends in the starting room?

Using the following graph, find an Euler circuit that begins and ends with vertex B.

What is the length of the following array? x = np.linspace(-1, 7, 23)

Which of the following is the relationship within sentence 11?

Consider the following code that we used to classify the income of adults in the US.inputs = tf.keras.layers.Dense(units=32, activation=’relu’, input_shape=) hidden = tf.keras.layers.Dense(units=32, activation=’relu’) outputs = tf.keras.layers.Dense(units=2, activation=TO BE FILLED) model = tf.keras.Sequential() loss = ‘sparse_categorical_crossentropy’ optimizer = tf.keras.optimizers.RMSprop(0.001) model.compile(loss=loss, optimizer=optimizer, metrics=)What was the activation function used on the output layer in this deep neural network?

Which of the following is the relationship between sentences six and seven?