/hslu-imath-exercises

HSLU - Lucerne University of Applied Sciences and Arts / Modul: IMATH (Informatik Mathematik)

Primary LanguageJupyter NotebookMIT LicenseMIT

HSLU - Modul: IMATH (Informatik Mathematik) - HS2019

HSLU - Lucerne University of Applied Sciences and Arts

Modul: IMATH (Informatik Mathematik) / HS2019

Content / Course material

  • root: per SW a jupyter notebook (with octave or octave cli) or python-files
    • Week_01 - Linear Algebra Part 1: From vectors to matrices and how to decompose matrices
    • Week_02 - Linear Algebra Part 2: The four fundamental subspaces and the complete solution of a linear system of equations
    • Week_03 - Linear Algebra Part 3: Determinant, Eigenvalues and -vectors, Singular Value Decomposition (SVD) useful in Machine Learning
    • Week_04 - Linear Algebra Part 4: Projective Geometry important in Computer Graphics
    • Week_05 - Multivariable Calculus Part 1: Graphing, Partial Derivatives, Gradient, Directional Derivative
    • Week_06 - Multivariable Calculus Part 2: (Total) Differential, Linearisation inkl. Application, Chain Rule
    • Week_07 - Multivariable Calculus Part 3: Higher-order Partial Derivatives, Critical Points, Optimization useful in Machine Learning
    • Week_08 - Numerics Part 1: Sources of errors, solving linear systems using direct and iterative methods
    • Week_09 - Numerics Part 2: Numerical integration, differentiation, approximation and extrapolation
    • Week_10 - Numerics Part 3: Approximation using trigonometric functions and splines
    • Week_11 - Numerics Part 4: The Discrete Fourier Transformation and the Fast Fourier Transform (FFT)
    • Week_12 - Ordinary Differential Equations (ODEs) Part 1: Definitions, Reduction of the Order
    • Week_13 - Ordinary Differential Equations (ODEs) Part 2: How to numerically solve a system of ODEs
    • Week_14 - Ordinary Differential Equations (ODEs) Part 3: some illustrative examples
    • Week_99 - Exam / MEP Preparation

Install Octave kernel for Jupyter

macOS

  1. Create virtual env using conda or other similar tools

  2. Install Jupyter Notebook and GNU Octave

brew install octave
brew install gnuplot
  1. Install octave kernel
pip install octave_kernel
  1. Check if the kernel is available
$ jupyter kernelspec list
Available kernels:
  octave     /Users/user/Library/Jupyter/kernels/octave
  python3    /Users/user/Applications/anaconda3/envs/imath/share/jupyter/kernels/python3
  1. Start Jupyther

jupyter notebook or jupyter lab, if available

In the notebook interface, select Octave from the 'New' menu