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()
Question
- 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()
Solution
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The best activation function for the output neuron in a multi-class classification problem, like the one described, is the softmax function. This is because the softmax function will give a probability distribution over the 4 classes, which is ideal for multi-class classification.
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All of the code snippets provided correctly calculate the average salary for each city. They all use the groupby function to group the data by city, and then calculate the mean of the 'Salary' column for each group. Therefore, the answer is "All of the above".
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