Différences

Ci-dessous, les différences entre deux révisions de la page.

--- teaching:methcalchim:start [2022/03/25 09:33] – [References] villersd
+++ teaching:methcalchim:start [2023/04/12 10:08] (Version actuelle) – [Classical numerical methods] villersd
@@ Ligne 122: / Ligne 122: @@
 + discussion of some approximations like [[wp>Bhaskara_I's_sine_approximation_formula|Bhaskara I's sine approximation formula]]
   * [[https://twitter.com/fermatslibrary/status/1267450081151782913]]
+  * [[https://medium.com/@mathcube7/chebyshev-interpolation-with-python-2f2e89bb7c30|Chebyshev Interpolation With Python]] Mathcube, Medium, 03/02/2023
 === Molecules modelisation and visualization ===
@@ Ligne 148: / Ligne 149: @@
   * Digital image processing, image recognition
     * particle tracking,...
+    * Voronoi diagrams, Delaunay triangulation,... ([[https://towardsdatascience.com/the-fascinating-world-of-voronoi-diagrams-da8fc700fa1b|ref1]])
@@ Ligne 186: / Ligne 188: @@
     * Fourier transforms : [[https://towardsdatascience.com/fourier-transforms-an-intuitive-visualisation-ba186c7380ee|Fourier Transforms: An Intuitive Visualisation - An intuitive visualization of discrete Fourier transforms applied to simple time-series data]] Diego Unzueta, Towards Data Science, Medium, 17/09/2021
     * Monte-Carlo simulations : [[Monte Carlo Simulation — a practical guide - A versatile method for parameters estimation. Exemplary implementation in Python programming language]] Robert Kwiatkowski, Medium, 31/01/2022
+    * régression logistique : [[https://mlu-explain.github.io/logistic-regression/]]
+    * [[https://towardsdatascience.com/cubic-splines-the-ultimate-regression-model-bd51a9cf396d|Cubic Splines: The Ultimate Regression Model - Why cubic splines are the best regression model out there]] Brendan Artley, Medium, 27/07/2022