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12 questions
Which of the following is a characteristic of supervised learning?
What is the main purpose of the loss function in a neural network?
Which regularization technique adds a penalty equivalent to the absolute value of the magnitude of coefficients?
Decision trees can be used for both classification and regression tasks.
Gradient descent always finds the absolute global minimum of the loss function in neural networks.
Support Vector Machines (SVMs) aim to find the hyperplane that maximizes the margin between classes.
Explain the difference between supervised and unsupervised learning.
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Describe how gradient descent updates the weights in a neural network during training.
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What is the purpose of regularization in machine learning models?
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Which of the following algorithms is an example of unsupervised learning?
Regularization techniques are used to reduce overfitting in machine learning models.
What role does a neural network's activation function serve in the learning process?
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