Consider the following array: a = np.array() If I want to select the last element of this array, what is the only option below that does not return me the element -55?

What is the main purpose of scaling your data?

Consider the following matrices:

Consider the following code to identify outliers:1)from sklearn.ensemble import IsolationForest 2)iforest = IsolationForest(random_state=0, contamination=0.05).fit(x) 3)y_iforest = iforest.predict(x) 4)idx = (y_iforest==1) 5)x_no_outliers = x 6)y_no_outliers = y 7)print(f’Total Number of Observations: {len(y)}’) 8)print(f’Total Number of Outliers: {len(y) – len(y_no_outliers)}’)Which line has the label without outliers?

The word ‘like’ has become hackneyed. Rather than being used sparingly, people use it as verbal filler between pauses of actual verbal information. The word hackneyed as it is used in the sentence most nearly means

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?