Question 1

Which algorithm is commonly used for generating synthetic data in machine learning?

Accepted Answer

Generative Adversarial Networks (GANs)

Answer

Random Forest

Answer

K-nearest neighbors (KNN)

Answer

Support Vector Machines (SVM)

Question 2

Which of the following is a popular algorithm used for natural language processing?

Accepted Answer

Recurrent Neural Networks (RNN)

Answer

K-means clustering

Answer

Random Forest

Answer

Decision Trees

Question 3

What is the concept of 'bias' in AI and Machine Learning?

Accepted Answer

Bias refers to the systematic error or prejudice that can be present in the data, algorithms, or decision-making processes, leading to unfair or discriminatory outcomes.

Answer

Bias refers to the random errors in the data or algorithms

Answer

Bias refers to the unbiased and neutral decision-making processes

Answer

Bias refers to the accuracy and reliability of the predictions

Question 4

What is the purpose of reinforcement learning in AI?

Accepted Answer

To train an agent to make sequential decisions to maximize a reward or achieve a goal through interaction with an environment

Answer

To classify and categorize data into different groups

Answer

To automate repetitive tasks

Answer

To learn from labeled training data and make accurate predictions

Question 5

What is overfitting in Machine Learning?

Accepted Answer

Overfitting occurs when a model performs very well on the training data but fails to generalize well to unseen data.

Answer

Overfitting occurs when a model performs poorly on the training data and also fails to generalize well

Answer

Overfitting occurs when a model performs equally well on both the training data and unseen data

Answer

Underfitting occurs when a model performs poorly on the training data but generalizes well to unseen data

Question 6

What is feature engineering in Machine Learning?

Accepted Answer

The process of selecting and transforming relevant features from raw data to improve model performance

Answer

The process of analyzing the results of a model

Answer

The process of training a model using labeled data

Answer

The process of evaluating model performance

Question 7

What is the curse of dimensionality in Machine Learning?

Accepted Answer

The phenomena where the performance of certain algorithms deteriorates with an increasing number of features or dimensions

Answer

The process of reducing the dimensionality of data in Machine Learning

Answer

The phenomena where the performance of certain algorithms improves with an increasing number of features or dimensions

Answer

The process of increasing the dimensionality of data in Machine Learning

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