AWS Academy Machine Learning - Module 3 Knowledge Check - 2025

Hey Folks, in this module we are going to see AWS Academy Machine Learning module 3 quiz answers. I am providing module 2 answers link below. 

Also Read: AWS Academy Machine Learning Module 2 Answers 

AWS Academy Machine Learning Module 3 

Q1. Which resources help define a machine learning ? (SELECT TWO)

A. Access to labeled data 

B. A domain expert to consult 

C. A traditional coded solution 

D. Sufficient Hardware 

E. A neural network 

Answer: [ A] , [ B ] 

               Access to labeled data 

               A domain expert to consult 

Q2. When preparing data for supervised classification machine learning, which attributes should 

       the data have? (SELECT TWO)

A. Data should be labeled 

B. Data should contain only instances of the target 

C. Anyone in the company should be able to access the data 

D. Data should be generated randomly by using genetic algorithms

E. Data should be representative of production 

Answer: [ A ] , [ E ] 

               Data should be labeled 

               Data should be representative of production 

Q3. What can you learn by examining the statistics of your data ? 

A. Identifying anamolies in the data 

B. Verifying that the data is formatted correctly 

C. Removing outliers 

D. Filling in missing Data 

Answer: [ A ]  Identifying anamolies in the data 

Q4. You have preprocessed dataset that's react for use in training a model. How should 

       you divide your training data ? 

A. Use all the data to train the model 

B. Split the data into two equal sets. Use one half for training and the other half for the testing. 

C. Split the data into three sets. Use 80% for training, 10% for testing and 10% for validation.

D. Split the data into two sets. Use 80% for training and 20% for testing and validation. 

Answer: [ C ] 

  Split the data into three sets. Use 80% for training, 10% for testing and 10% for validation. 

Q5.You can select between single model and multi - model hosting with Amazon Sage Maker. 

A. True 

B. False 

Answer: [ A ]  True 

Q6. What is the Purpose of a confusion matrix ? 

A. To plot the labels from the Predicts dataset. 

B. To show the true or false positives, along with the true or false negatives

C. To show the correlation between two columns in the dataset.

D. To stratly the Classes across training and testing data sets.

Answer: [ B ]  To show the true or false positives, along with the true or false negatives

Q7. What does the correlation heatmap show?

A. The level of correlation between features in a dataset 

B. The level of correlation between the test and the validation data 

C. The level of correlation between the predicted and the actual values

D. The level of correlation between encoded and text data 

Answer: [ A ]  The level of correlation between features in a dataset 

Q8. Which of the following file formats does pandas support for data importing ? 

       ( SELECT TWO ) 

A. JSON 

B. MS Word 

C. CSV 

D. Binary files 

E. PDF 

Answer: [ A] , [ C ]   JSON , CSV 

Q9. Which Amazon service can you use to deploy machine learning instances and run 

       Jupyter Notebooks ? 

A. Amazon Comprehend 

B. Amazon Sage Maker 

C. Amazon Polly 

D. Amazon Lex 

Answer: [ B ]  Amazon Sage Maker 

Q10. What is the goal of an Amazon Sage Maker hyperparameter tuning job ? 

A. To optimize metrics for training. 

B. To optimize the model parameters to produce the best model 

C. To optimize the data inputs to produce the fastest prediction 

D. To optimize the algorithm choice to produce the best model. 

Answer: [ B ] To optimize the model parameters to produce the best model 

Also Read: AWS Academy Machine Learning Module 2 Answers 

Conclusion 

In the Next Module we are going to discuss about the Module 4 Answers with 100% Guarantee.