Supervised, unsupervised and reinforcement learning, training and test splits, bias and variance, cross-validation and the ML workflow.
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- What is supervised learning?
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Learning from labeled training data where each example has a target output.- What is a label or target in supervised learning?
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The correct output value that a model is trained to predict for each example.- What is the difference between regression and classification?
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Regression predicts continuous values, classification predicts discrete categories.- Give an example of a regression task.
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Predicting house prices, stock prices, temperature, or any continuous numerical value.- Give an example of a classification task.
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Predicting whether an email is spam, whether an image contains a cat, or which disease a patient has.- What is a feature in supervised learning?
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An input variable or attribute used by a model to make predictions.- What is overfitting?
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A model that learns noise in the training data and performs poorly on new, unseen data.- What is underfitting?
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A model that is too simple to capture the underlying patterns in the data.- What is unsupervised learning?
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Learning from unlabeled data to find hidden patterns or structure without target outputs.- What is clustering?
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Grouping data points into clusters based on similarity, with points in the same cluster being more similar to each other than to points in other clusters.- What is the general idea behind k-means clustering?
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Partition data into k clusters by iteratively assigning points to the nearest centroid and updating centroids based on cluster membership.- What is dimensionality reduction?
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A technique to reduce the number of features or variables in a dataset while preserving important information.- Give an example of an unsupervised learning task.
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Customer segmentation, document clustering, image compression, or anomaly detection.- What is the key difference between supervised and unsupervised learning?
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Supervised learning uses labeled data with target outputs, while unsupervised learning works with unlabeled data.- What is a cluster in the context of unsupervised learning?
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A group of data points that are similar to each other and dissimilar to points in other clusters.
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