WorksheetsQuiz on Machine Learning Concepts
Total questions: 20
Worksheet time: 10mins
Which type of machine learning requires labeled data to train the model?
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Semi-supervised Learning
In unsupervised learning, the dataset consists of:
Only output labels
Input features and output labels
Only input features
Only output features
Which algorithm is commonly used in unsupervised learning?
Linear regression
Decision trees
K-Means clustering
Logistic regression
What is the output of a supervised learning model trained to detect email spam?
The email content
Spam or not spam
The sender's address
The number of emails
Which of the following is a real-world application of unsupervised learning?
Predicting house prices
Email spam detection
Grouping customers based on purchasing behavior
Image classification
Which machine learning technique is best suited for anomaly detection in banking transactions?
Supervised learning
Unsupervised learning
Reinforcement learning
Transfer learning
What is the first step in supervised learning?
The model predicts outputs for new data
The dataset consists of input features and output labels
The model looks for groupings in the data
The model reduces dimensionality
Which of the following is a common use case for supervised learning?
Reducing the dimensionality of data
Grouping customers
Predicting house prices
Identifying fraudulent transactions
Which of the following is a feature of unsupervised learning?
Requires labeled data
Works with unlabeled data
Learns a mapping from inputs to outputs
Used only for regression tasks
What is the output of an unsupervised learning model that performs clustering?
Predicted labels for new data
Groupings or clusters of data points
Regression coefficients
Classification accuracy
Which of the following statements is true about supervised learning?
It works only with unlabeled data
It is used to identify patterns without predefined outputs
It requires input-output pairs for training
It cannot be used for prediction tasks
Which formula is used to update weights during backpropagation?
W_new = W_old - η * ∂Error/∂W
W_new = W_old + η * ∂Error/∂W
W_new = W_old * η * ∂Error/∂W
W_new = W_old / η * ∂Error/∂W
What does the learning rate (η) control in the weight update formula?
How much the weights are adjusted
The number of layers in the network
The type of activation function used
The size of the input data
Which type of regression models the relationship between variables as a straight line?
Linear regression
Polynomial regression
Logistic regression
Ridge regression
Which of the following is an example of a use case for linear regression?
Predicting house prices based on size
Classifying emails as spam or not spam
Clustering customers by purchasing behavior
Reducing the number of features in a dataset
What is the main difference between linear regression and polynomial regression?
Linear regression models straight-line relationships, while polynomial regression models non-linear relationships
Linear regression is used for classification, while polynomial regression is used for clustering
Linear regression uses binary output, while polynomial regression uses categorical output
Linear regression requires more data than polynomial regression
What is the chain rule of calculus used for in backpropagation?
To calculate the gradient of error with respect to weights
To determine the number of layers in the network
To select the activation function
To normalize the input data
Which optimization algorithm is commonly used to update weights in backpropagation?
Gradient Descent
K-Means
Principal Component Analysis
Random Forest
Which of the following is a domain where regression is commonly used?
Finance (stock predictions)
Image segmentation
Clustering customers
Sorting algorithms
What is the output variable called in regression analysis?
Predicted output (y)
Input feature (x)
Slope (m)
Intercept (c)
