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1806

18.06 course at MIT

18330

18.330 Introduction to Numerical Analysis

18337

18.337 - Parallel Computing and Scientific Machine Learning

18s096sciml

18.S096 - Applications of Scientific Machine Learning

18s191

Course 18.S191 at MIT, Spring 2021 - Introduction to computational thinking with Julia:

6s083

Materials for MIT 6.S083 / 18.S190: Computational thinking with Julia + application to the COVID-19 pandemic

afe2020

Advanced Financial Econometrics - Trinity Term 2020

algforopt-notebooks

Jupyter notebooks associated with the Algorithms for Optimization textbook

bootcamp2018

Repository of syllabi, lecture notes, Jupyter notebooks, code, and problem sets for OSM Lab Boot Camp 2018

bootcamp2019

Repository of syllabi, lecture notes, Jupyter notebooks, code, and problem sets for OSE Lab Boot Camp 2019

bvar_

Empirical macro toolbox

compecon2020

Computational Economics Course 2020 by Kenneth Judd

compecon_fall19

ECON 815: Computational Methods for Economists

compeconworkshop_2017

computational-methods-in-macro

PhD level course on advanved macro models dealing with agent heterogeneity.

coursera-applied-data-science-with-python

Repository for coursera specialization Applied Data Science with Python by University of Michigan

coursera-stanford

Stanford

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-models

Keras code and weights files for popular deep learning models.

deep-learning-specialization-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

dlaicourse

Notebooks for learning deep learning

dsge.jl

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

dsge_mod

A collection of Dynare models

econometric_theory_slides

Slides for A Primer in Econometric Theory

econometrics

Code and notebooks for Econometric Theory

econpdes.jl

Solve semi-linear parabolic PDEs

figures

R code for figures on Statistics with R slides

financial-frictions

Interactive guide to Fernández-Villaverde, Hurtado, and Nuño (2019): "Financial Frictions and the Wealth Distribution".

gian-applied-nla-course

Materials for the GIAN Course "Modern Applications of Numerical Linear Algebra Methods"

interactive-data-visualization-with-python

Present your data as an effective and compelling story