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WorksheetsMl based
Total questions: 10
Worksheet time: 11mins
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
