HSLU - Lucerne University of Applied Sciences and Arts
Modul: IMATH (Informatik Mathematik) / HS2019
root
: per SW a jupyter notebook (with octave or octave cli) or python-filesWeek_01
- Linear Algebra Part 1: From vectors to matrices and how to decompose matricesWeek_02
- Linear Algebra Part 2: The four fundamental subspaces and the complete solution of a linear system of equationsWeek_03
- Linear Algebra Part 3: Determinant, Eigenvalues and -vectors, Singular Value Decomposition (SVD) useful in Machine LearningWeek_04
- Linear Algebra Part 4: Projective Geometry important in Computer GraphicsWeek_05
- Multivariable Calculus Part 1: Graphing, Partial Derivatives, Gradient, Directional DerivativeWeek_06
- Multivariable Calculus Part 2: (Total) Differential, Linearisation inkl. Application, Chain RuleWeek_07
- Multivariable Calculus Part 3: Higher-order Partial Derivatives, Critical Points, Optimization useful in Machine LearningWeek_08
- Numerics Part 1: Sources of errors, solving linear systems using direct and iterative methodsWeek_09
- Numerics Part 2: Numerical integration, differentiation, approximation and extrapolationWeek_10
- Numerics Part 3: Approximation using trigonometric functions and splinesWeek_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 OrderWeek_13
- Ordinary Differential Equations (ODEs) Part 2: How to numerically solve a system of ODEsWeek_13
- Ordinary Differential Equations (ODEs) Part 3: some illustrative examplesWeek_99
- Exam / MEP Preparation
-
Create virtual env using conda or other similar tools
-
Install Jupyter Notebook and GNU Octave
brew install octave
brew install gnuplot
- Install octave kernel
pip install octave_kernel
- 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
- Start Jupyther
jupyter notebook
or jupyter lab
, if available
In the notebook interface, select Octave from the 'New' menu