Which ONE of the following options is an example that BEST describes a system with Al-based autonomous functions?
SELECT ONE OPTION

• A.A system that utilizes human beings for all important decisions.
• B.A fully automated manufacturing plant that uses no software.
• C.A system that utilizes a tool like Selenium.
• D.A system that is fully able to respond to its environment.

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"AllerEgo" is a product that uses sell-learning to predict the behavior of a pilot under combat situation for a variety of terrains and enemy aircraft formations. Post training the model was exposed to the real- world data and the model was found to be behaving poorly. A lot of data quality tests had been performed on the data to bring it into a shape fit for training and testing.
Which ONE of the following options is least likely to describes the possible reason for the fall in the performance, especially when considering the self-learning nature of the Al system?
SELECT ONE OPTION
The difficulty of defining criteria for improvement before the model can be accepted.
The fast pace of change did not allow sufficient time for testing.
The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
There was an algorithmic bias in the Al system.

• A.The difficulty of defining criteria for improvement before the model can be accepted.
  Defining criteria for improvement is a challenge in the acceptance of AI models, but it is not directly related to the performance drop in real-world scenarios. It relates more to the evaluation and deployment phase rather than affecting the model's real-time performance post-deployment.
• B.The fast pace of change did not allow sufficient time for testing.
  This can significantly affect the model's performance. If the system is self-learning, it needs to adapt quickly, and insufficient testing time can lead to incomplete learning and poor performance.
• C.The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
  This is highly likely to affect performance. Self-learning AI systems require detailed specifications of the operating environment to adapt and learn effectively. If the environment is insufficiently specified, the model may fail to perform accurately in real-world scenarios.
• D.There was an algorithmic bias in the AI system.Algorithmic bias can significantly impact the performance of AI systems. If the model has biases, it will not perform well across different scenarios and data distributions.

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A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.
Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
SELECT ONE OPTION

• A.Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.
• B.Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
• C.Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.
• D.Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.

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Which ONE of the following options is the MOST APPROPRIATE stage of the ML workflow to set model and algorithm hyperparameters?
SELECT ONE OPTION

• A.Evaluating the model
• B.Deploying the model
• C.Tuning the model
• D.Data testing

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Which ONE of the following combinations of Training, Validation, Testing data is used during the process of learning/creating the model?
SELECT ONE OPTION

• A.Training data - validation data - test data
• B.Training data - validation data
• C.Training data * test data
• D.Validation data - test data

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