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CodeSignal

Basic Linear Algebra with SciPy

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Overview

This course introduces participants to SciPy’s linear algebra capabilities, focusing on solving linear equations, understanding eigenvalues and eigenvectors, matrix decomposition, and working with sparse matrices. By the end of the course, learners will gain a practical understanding of applying linear algebra solutions effectively in Python.

Syllabus

  • Unit 1: Vector Norm, Matrix Determinant, and Inverse Matrix with SciPy
    • Comparing Vector Magnitudes with Norms
    • Calculating L1 Norm in SciPy
    • Determinant for System Solvability
    • Calculate the Inverse of a Matrix
  • Unit 2: Solving Linear Equation Systems with SciPy
    • Represent Linear Equations with Matrices
    • Verify Your Linear Equation Solution
    • Solving Linear Equations Made Simple
  • Unit 3: Eigenvalues and Eigenvectors with SciPy
    • Visualizing Eigenvectors with Plotting
    • Complete the Eigenvalue Challenge
    • Exploring Eigenvectors with Python
  • Unit 4: Matrix Decomposition with SciPy
    • Matrix Decomposition Mastery
    • Break Down the Matrix
    • Matrix Decomposition Validation Task
    • Matrix Mastery with SVD Decomposition
    • Recompose a Matrix with SVD

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