NU Data Science Club

Point out the correct statement:

• Machine learning focuses on prediction, based on known properties learned from the training data

• Data Cleaning focuses on prediction, based on known properties learned from the training data.

• Representing data in a form which both mere mortals can understand and get valuable insights is as much a science as much as it is art

• None of the Mentioned

Sequential Modelling is done on:

• ANN

• CNN

• RNN

• KNN

Positive Correlation:

• Below -0.8

• Above 0.8

• Above -0.8

• Below 0.65

  
  

Which of the following can be considered as random variable?

• The outcome of flip of a coin

• The outcome of exam

• The outcome from the roll of a die

• All of the Mentioned
  

What is feature engineering in machine learning?

• A process of designing new machine learning algorithms

• A process of selecting the most important features in the dataset

• A process of creating new features or transforming existing features to improve model performance

• A process of reducing the dimensionality of the dataset

Which of the following algorithms is a supervised learning algorithm?

• K-means clustering

• Principal Component Analysis (PCA)

• Apriori algorithm

• Decision tree

What is the purpose of regularization in machine learning?

• To prevent overfitting

• To improve model interpretability

• To increase model complexity

• To reduce computational resources

What does the bias-variance tradeoff refer to in machine learning?

• The tradeoff between model simplicity and model complexity

• The tradeoff between the model's ability to capture the underlying patterns in the data and its sensitivity to noise

• The tradeoff between the number of features and the number of instances in the dataset

• The tradeoff between model performance on training data and unseen data

What is the purpose of the 'train-test split' in machine learning?

• To divide data into two sets for training and testing the model

• To reduce the size of the dataset

• • To train the model twice as fast

• To test the model's performance in real-time

What does 'PCA' stand for in data science?

• Predictive Component Analysis

• Process Component Analysis

• Principal Component Analysis

• Python Component Analysis