FabrizioMusacchio

Python_Course

This is the course material for the introductory course into Python basics for Data Scientists.

Python_Neuro_Practical

This is the course material for the advanced course into Python for Data Scientists.

Mastodon_powered_comments

This repository contains a HTML script including liquid commands and JavaScript, that integrates a Mastodon-powered comment system into a static website. The script is written in a way that it can be used with the static site generator Jekyll.

Napari_Bioimage_Analysis

Image data and Python scripts for the course on Bioimage analysis with Napari

bio_image_registration

Scripts for evaluating common Python image registration methods

fractals

This repository contains the code for the blog post on The Weistrass function and the beauty of fractals. For further details, please refer to this post.

SIR_model

This repository contains the code for the blog post on The SIR model: A mathematical approach to epidemic dynamics. For further details, please refer to this post.

ann_with_numpy

A how-to for building an artificial neural network from scratch using NumPy

dimensionality_reduction

Code used in blog post about dimensionality reduction using Python

earth_magnetic_field

The code in this repository is modified after scipython.com. It plots Earth's dipolar magnetic field and was used in the blog post on Earth's dipolar magnetic field. For further details, please refer to this post.

entropy

This repository contains the code for the blog post on Understanding entropy. For further details, please refer to this post.

fabriziomusacchio

OASIS

Deconvolution of calcium imaging data

Python_Performance_Tests

A collection of script for basic performance tests in Python.

Gradient_Descent

This repository contains the code for the blog post on Understanding gradient descent in machine learning. For further details, please refer to this post.

Hodgkin-Huxley-Model

Python scripts supporting a tutorial on the Hodgkin-Huxley model.

hopfield_network

In this tutorial, we explore the mathematical underpinnings of Hebbian learning within Hopfield networks, emphasizing its role in pattern recognition.

integrate_and_fire_model

izhikevich_model

Python scripts supporting tutorials on Izhikevich neuron model.

L1_and_L2_regularization

This repository contains the code for the blog post on Understanding L1 and L2 regularization in machine learning. For further details, please refer to this post.

Lorenz_Attractor

This repository contains the code for the blog post on Solving the Lorenz system using Runge-Kutta methods. For further details, please refer to this post.

lotka_volterra_equations

This repository contains the code for the blog post on The Lotka-Volterra equations: Modeling predator-prey dynamics. For further details, please refer to this post.

machine_learning_for_image_denoising

This repository contains the Python code my blog post Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN. See post for more details and results.

Orbit

This repository contains the code for the blog post on Runge-Kutta methods for solving ODEs. For further details, please refer to this post.

phase_plane_analysis

Python scripts supporting tutorials on phase plane analysis.

Random_Forest_vs_Decision_Tree

Code used in two blog posts on decision trees and random forests.

roessler_attractor

Just a simple Python code example for simulating the trajectory of the Rössler attractor.

runge_kutta_methods

Wasserstein_distance_demo

This repository contains the code for some blog posts on the Wasserstein metric. For further details, please refer to the corresponding posts.

wasserstein_gan

This repository contains some code for demonstrating the application of Wasserstein GANs (WGANs)