3 Questions
What is the difference between supervised and unsupervised machine learning?
Supervised learning is a type of machine learning where the model is trained using labeled data, while unsupervised learning is a type of machine learning where the model is trained using unlabeled data.
What is overfitting in machine learning?
Overfitting in machine learning occurs when a model is trained too well on a particular dataset, to the point where it starts to fit noise in the data rather than the underlying pattern.
What is gradient descent in machine learning?
Gradient descent is an optimization algorithm used in machine learning to minimize the error of a model by iteratively adjusting the model's parameters in the opposite direction of the gradient of the error function.
Challenge your knowledge of machine learning with this quiz! Learn about the differences between supervised and unsupervised learning, understand the concept of overfitting, and test your understanding of gradient descent. Get ready to dive deep into the world of machine learning and improve your skills in this fascinating field.
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