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What is One Hot Encoding?  

Which syntax is used to fill missing value with number 5 in dataframe “df”?  

For the example of Linear Regression, how do you train a dataset applying Linear Regression? Let’s label Linear Regression as “LR”.   X_train & Y_train are training dataset and corresponding label  X_test & Y_test are testing dataset and corresponding label  

In the K-Nearest-Neighbor algorithm, how do you specify how many data points to evaluate (K – Hyperparameter)  to determine which class the data point belongs to? In this example, let’s say we want to evaluate 5 dat apoints.  

How do you get the data type for each column in a data frame (df)?    

What type of function does Logistic Regression use to define its decision boundary between different data points?

Python allows string slicing. What is the output of the following code: s=”Applied Machine Learning” print(s[3:5])

What can go wrong if you tune hyperparameters using the test set?

Write a function rmse that takes in truth and prediction values and returns the root-mean-squared error. Use sklearn’s ‘mean squared error’ class. All variables are as per assignment   A. from sklearn.metrics import mean_squared_error def rmse(ytrue):     return np.sqrt(mean_squared_error(ytrue, ypredicted))   B. from sklearn.metrics import mean_squared_error def rmse(ytrue, ypredicted):     return np.sqrt(mean_squared_error(ypredicted))   C. from sklearn.metrics import mean_squared_error def rmse(ytrue, ypredicted):     return np.sqrt(mean_squared_error(ytrue, ypredicted))   D. from sklearn.metrics import mean_squared_error def rmse(ypredicted):     return np.sqrt(mean_squared_error(ytrue, ypredicted))

Which of the following code is the correct way to transpose data?