Machine Learning Fundamentals · free preview
The Linear Model
A linear model predicts a target as a weighted sum of the features plus a bias, and one matrix-vector product computes the predictions for a whole dataset.
1. From a weighted sum to a dot product
From a weighted sum to a dot product
2. One matrix product for the whole dataset
One matrix product for the whole dataset
3. The assumption behind the numbers
The assumption behind the numbers
4. What the bias term is for
A linear regression model is fitted to predict house price from area and age. The bias term is kept in the model. Which statement describes what contributes?
5. Reading the design matrix
A dataset has examples and features. Its design matrix has shape ____.
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