Which of the following is an example of Supervised Learning?

• Detecting spam emails based on past labeled data

• Grouping customers based on their shopping behavior

• A robot learning to walk through trial and error

• Identifying hidden patterns in unstructured data

What does Overfitting mean in Machine Learning?

• The model performs well on new data but poorly on training data

• The model memorizes training data but fails to generalize to new data

• The model has too little data to train on

• The model is too simple and performs poorly on all data

What is the key difference between Traditional Programming and Machine

Learning?

• Traditional programming learns from data, while ML follows fixed rules

• Machine Learning is faster in all cases than traditional programming

• Machine Learning learns from data and improves over time, while Traditional

  Programming follows predefined rules

• Traditional programming always requires a neural network

Which of the following is an example of Reinforcement Learning?

• A self-driving car learning to navigate by getting rewards for good actions

• A spam filter that classifies emails as spam or not spam

• Grouping customers based on their purchase behavior

• Identifying whether a person has cancer based on medical records

What is the main advantage of Machine Learning?

• It eliminates all human decision-making

• It can identify patterns and make predictions from large datasets

• It is always 100% accurate

• It requires no data to function

Which is not an advantage of Data Preprocessing?

• Improving the data quality

• Enhancing model performance

• Reducing Computational Complexity

• Introducing bias into the dataset

Which is the correct order of Data Preprocessing?

1. Data Formatting and Data Binning.

2. Importing the Dataset and getting Basic insights.

3. Dealing with Categorical Values.

4. Dealing with Null Values.

5. Feature Scaling.

6. Splitting of the Dataset. (For Training & Testing)

• 2, 4, 1, 3, 6, 5

• 1, 2, 3, 4, 5, 6

• 2, 4, 1, 3, 5, 6

• 2, 3, 4, 1, 6, 5

How to show the first 5 rows in the dataset in dataframe named “df”?

• df.head()

• df.head(5)

• df.tail()

• both a & b

Which of the following ways is not a method of dealing with null values?

• drop the data (either row or column)

• replace the data with mean

• replace the data with a random value

• replace the data with most frequent value

What is the main purpose of feature engineering in data preprocessing?

• To remove all missing values without considering their impact

• To create relevant features that improve model performance

• To randomly add new features without domain knowledge

• To introduce noise into the dataset