Chapter 2: Linear Algebra Refresher

A quick refresher on linear algebra concepts essential for neural networks:

  • Scalars, Vectors, Matrices, and Tensors: The fundamental data structures.
  • Multiplying Matrices and Vectors: Dot products are everywhere!
  • Identity and Inverse Matrices: $A^{-1}A = I$
  • Linear Dependence and Span: Understanding the column space of a matrix.
  • Eigendecomposition: Decomposing a matrix into its eigenvalues and eigenvectors.
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