Supervised Learning

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"(1) Paradigms of supervised learning
(2) Binary classification
(3) Multiclass classification
(4) Regression"
  1. IIT Madras - B.S. Degree Programme
  2. "Features
  3. attributes
  4. labels
  5. binary classification
  6. multiclass classification
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Man Arun sir's teaching, ability to explain stuff, and even the variety of shirts he wears are all top-notch.

saranshsaini
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In the lecture, X is shown as a matrix with n elements as columns, and d features as rows.
However in most practical situations, the dataset will be n rows x d columns.

If you try to implement the algorithm in code (using numpy), please swap "X_Transpose" shown in the lecture with "X"

MiMoMa-cr