Stars
Neural Networks: Zero to Hero
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
Notebooks for "Python for Signal Processing" book
A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.
Quantitative Interview Preparation Guide, updated version here ==>
Numerical Tours of Signal Processing
Pilot course for Robotics 101: Computational Linear Algebra
Introduction to Mathematical Computing with Python and Jupyter
Materials for MIT 6.S083 / 18.S190: Computational thinking with Julia + application to the COVID-19 pandemic
Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.
A short course on Julia and open-source software development
GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich
Some code examples gathered during my Month of Julia.
Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen
A collection of RAPIDS examples for security analysts, data scientists, and engineers to quickly get started applying RAPIDS and GPU acceleration to real-world cybersecurity use cases.
Notebook for running Julia on Google Colab
Code to accompany the textbook "Modeling Neural Circuits Made Simple"
Data science teaching materials
A jupyter notebook with some stuff on the FT
Training spiking neural networks for sound localization
A collection of code and lessons for the KCNI Summer School
A short course for getting started with deep learning for intracranial extracellular neurophysiology.
Dynamic Causal Modelling for MNE and the nipy ecosystem