A fixed income analyst is trying evaluating the probablity of default of a high yield bond using a neural network. Which type of activation function would he be LEAST likely to use?ALinear functionBLogistic functionCHyperbolic functionDRELU Function

Which of the following activation functions is primarily used for neural networks designed to classify binary data?a)Hyperbolic tangent (tanh) functionb)Sigmoid functionc)Rectified Linear Unit (ReLU)d)Softmax function

Suppose we use a neural network to classify images of handwritten digits (0-9). Which of the following activation functions is most suitable at the output layer? Softmax ReLU Tanh Sigmoid

The ______________ function is often used as an activation function in the output layer of a binary classification problem.

8.  A machine learning specialist is training a deep neural network to classify an image into one of the 4 categories available. Which of the following is the best activation functions the specialist can use in the output neuron?softmaxrelusigmoidlinear9. import pandas as pddf =pd.DataFrame( { 'Name': ['Alice', 'Bob', 'Charlie', 'Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35, 25, 30, 35], 'City': ['New York', 'Los Angeles', 'Chicago', 'New York', 'Los Angeles', 'Chicago'], 'Salary': [70000, 80000, 90000, 75000, 85000, 95000]})Which of the following code snippets correctly calculates the average salary for each city?df.groupby('City').Salary.mean()All of the aboveNone of the abovedf.groupby('City', as_index=False)['Salary'].mean()df.groupby('City').agg({'Salary': 'mean'})df.groupby('City')['Salary'].mean()

What is the purpose of the activation function in a neural network?Review LaterTo determine the learning rateTo normalize the input dataTo introduce non-linearityTo calculate the loss function