Scientific Programming
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Tutorials and applications from scientific programming

https://github.com/Ziaeemehr
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🔆 STAN
☘️ Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation.
☘️ Stan interfaces with the most popular data analysis languages (R, #python, shell, MATLAB, Julia, Stata) and runs on all major platforms (Linux, Mac, Windows).

🌱 Stan User’s Guide
🌱 PyStan Guide
To install simply use:
$ pip3 install pystan
Bernstein Network Computational Neuroscience

We are extremely happy to let you know that the registration for the #BernsteinConference 2020 is now open! This year, the conference is free of charge but registration is mandatory.
Link
ALLEN INSTITUTE MODELING WORKSHOP
The workshop will run from Wednesday, August 12 to Friday, August 14, and begin at 8am Pacific Time each day (7:30 PM in Tehran Time)
Spiking neural networks as universal function approximators: Learning algorithms and applications
(Aug 31st / Sep 1st 2020)

The last years have seen many exciting new developments to train spiking neural networks to perform complex information processing. This online workshop brings together researchers in the field to present their work and discuss ways of translating these findings into a better understanding of neural circuits. Topics include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing. We have a manageable number of talks with ample time for discussions.

The workshop is being organised by Dan Goodman and Friedemann Zenke.
Register here

#workshop
I am working on Modeling neural dynamics from Borgers using #brian2.

It's easy to learn and fast for development.
for a quick review and tutorial look at here.
There is also a course by #Gerstner which use brain2 in his book. [link to exercise]
The course is available by EPFL.
I am uploading the jupyter note books of Borgers using brian2 here.
Have fun coding!
Brian workshop, 9 Sep, 16-19 Iran time.
The material will be uploaded here.
To install the required package look here.

Please fill the google form for the registration (free of charge).
(Register)
The language of workshop will be in Farsi (Excuseme nonpersian members).
(Add to google calendar)
🍀 Sept 2020 / Python for Scientist

This is a medium-advanced course in Python tools such as NumPy, SciPy, Matplotlib, and Pandas. It is suitable for people who have a basic understanding of basic Python and want to know some internals and important libraries for science. 

https://scicomp.aalto.fi/training/scip/python-for-scicomp/
🔆 Scientific Programming with Python and Software Engineering Best Practices

🌱 Advanced Numpy
🌱 Introduction to predictive analytics with Pandas and Scikit Learn
🌱 Testing, debugging, profiling
🌱 Packaging and continuous integration

https://telecom-python.telenczuk.pl/materials
🍀 The Algorithms - Python


A beautiful and well-maintained repository of some classic and well-known algorithms from many different domains. This resource can help you understand how to implement algorithms while practicing programming using Python.

https://github.com/TheAlgorithms/Python
@omarsar0
Information theory and self-organisation -- a course on theory and empiricial analysis using the JIDT software

This playlist presents video lectures from a course on using information theory for analysing complex systems, with particular focuses on:
1. Measures of information dynamics: how information is processed in complex systems, including measures of information storage and transfer;
2. Empirical data analysis using the JIDT open-source software - https://github.com/jlizier/jidt

Full course overview, slides and activities will be available from the JIDT wiki at
https://github.com/jlizier/jidt/wiki/Course