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WorksheetsDataQuest_Quiz
Total questions: 15
Worksheet time: 8mins
Among the following options identify the one which is not a type of learning?
Supervised Learning
Semi unsupervised Learning
Reinforcement Learning
Semi supervised Learning
What is the application of machine learning methods to a large database called?
Big Data Computing
Internet of Things
Data Mining
Artificial Intelligence
Which of the following machine learning algorithm is based upon the idea of bagging?
Decision Tree
Random Forest
Regression
Classification
Choose a disadvantage of decision trees among the following.
Decision trees are robust to outliers
Factor Analysis
Decision Trees are prone to overfit
All of the above
The father of Machine Learning is
Geoffrey Everest Hinton
Geoffrey Hill
Geoffrey Chaucer
None of the above
FIND-S algorithm ignores?
Positive
Negative
Both
None
The total types of the layer in the radial basis function neural networks is
1
3
2
4
What does K stand for in the K mean algorithm?
Number of clusters
Number of data
Number of attributes
Number of iterations
Which of the following is not a supervised learning?
PCA
Linear Regression
Decision Tree
Naive Bayesian
Among the following option, identify the one which is used to create the most common graph types?
plot
quickplot
qplot
All of the above
What is the primary purpose of the activation function in a neural network?
To normalize the input data
To determine the learning rate
To reduce overfitting
To introduce non-linearity
In a feedforward neural network, which layer(s) typically have no recurrent connections?
Input Layer
Hidden Layer
Output Layer
All layers have recurrent connections
What is the backpropagation algorithm used for in neural networks?
Initializing network weights
Training the network to minimize error
Regularizing the network
Generating random data for testing
Which type of neural network architecture is commonly used for image recognition tasks?
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Long Short-Term Memory (LSTM)
Autoencoder
Which technique is used to prevent overfitting in neural networks by randomly deactivating a fraction of neurons during training?
Batch Normalization
Gradient Clipping
Dropout
L1 Regularization
