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opensees_python

Opensees_Python

openseespy-examples

This is a more pythonic implementation of OpenSeesPy library to model and analyze structural problems in Jupyter notebooks

openseespydoc

OpenSeesPy Documentation

oq-engine

OpenQuake's Engine for Seismic Hazard and Risk Analysis

overleaf-sync

Overleaf Two-Way Synchronization

pandas_exercises

Practice your pandas skills!

portal

The DesignSafe-CI Portal

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

protected-github-pages

Password protected GitHub pages

pycufsm

Python port of CUFSM (Constrained and Unconstrained Finite Strip Method), for analysing the buckling of thin-walled structures.

pyprobml

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

pyre

Structural Reliability Analysis with Python

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

rsb-illustration

Scripts and data related to an illustration of the use of a modular decision framework to support early resilient and sustainable design of a hypothetical mid-rise office building located in Charleston, SC

sciann-applications

A place to share problems solved with SciANN

scikit-learn-videos

Jupyter notebooks from the scikit-learn video series

shiarthur03

shishitao

My personal repository

simcenterai_workshop2021

smartanalyze

Helper function to boost OpenSees analyze.

stanford-cs-229-cn

A Chinese Translation of Stanford CS229 notes 斯坦福机器学习CS229课程讲义的中文翻译

statistical-learning-and-machine-learning-with-r

:books: Statistical Learning R Labs

structpy

Structural Analysis Library for Python based on the direct stiffness method

tcljupyter

Tcl kernel for Jupyter

the-elements-of-statistical-learning-notebooks

Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman

ucsd_louis

xuan