Classification predicts a category (discrete output). Regression predicts a continuous numerical value.
Tag
#ml
What is the difference between classification and regression?
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What is a neural network and how does it learn?
A neural network is a series of connected layers of mathematical functions (neurons) that transform inputs into outputs. It learns by adjusting the connection weights using backpropagation — computing how…
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How does a Random Forest work and why is it better than a single decision tree?
A Random Forest builds many decision trees on random subsets of data and features then aggregates their predictions. It is better than a single tree because averaging many uncorrelated trees…
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How would you explain the importance of CI/CD pipelines in the context of deploying AI and machine learning models?
CI/CD pipelines are crucial for AI and machine learning because they automate the deployment process, ensuring that models can be reliably and quickly delivered to production. This allows for consistent…
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What is a training set validation set and test set — and why do you need all three?
Training set is used to fit the model. Validation set is used to tune hyperparameters and select the best model. Test set is held out completely and used only once…
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What is attention mechanism and why did it replace RNNs for sequence modeling?
Attention allows a model to directly reference any position in the input sequence when processing each output token regardless of distance. RNNs process sequentially and lose information about distant tokens.…
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