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-datasciencecoursera

This is the first project for Coursera

addaandcooper

Code to solve exercises from Adda and Cooper's "Dynamic Economics" book

ai_curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

airbnb

Project analyzing Airbnb Rental data

airbnb-dynamic-pricing-optimization

[BA project] Dynamic Pricing Optimization for Airbnb listing to optimize yearly profit for host. Use Clustering for competitive analysis, kNN regression for demand forecasting, and find dynamic optimal price with Optimization model.

aiyagaricontinuoustime.jl

Solve Aiyagari Model in Continuous Time

applied_computational_economics_and_finance

ECON457 2018 Applied Computational Economics and Finance

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

autograd

Efficiently computes derivatives of numpy code.

automatestuff-ja

『退屈なことはPythonにやらせよう』のリポジトリ

awesome-cryptoeconomics

An awesome curated list of Cryptoeconomic research and learning materials

bayesian_methods_julia

「Pythonで体験するベイズ推論」をJuliaでやってみる

behavioral_heterogeneity

Replication data and code for "Structural Estimation of Behavioral Heterogeneity"

behavioraleconomics

R package for behavioral economics

bertpractice

bkm_mit

Code to Implement the Algorithm in "Exploiting MIT Shocks in Heterogeneous-Agent Economies: The Impulse Response as a Numerical Derivative" by Timo Boppart, Per Krusell and Kurt Mitman

blp-demand

estimate BLP demand model in Matlab using state-of-the-art techniques

blp-demand-estimation

Python code for BLP (Berry, Levinsohn and Pakes) method of structural demand estimation using the random-coefficients logit model. Code for estimation of demand and supply-side moment jointly is also provided.

blp-python

BLP-Python provides an implementation of random coefficient logit model of Berry, Levinsohn and Pakes (1995)

brookingspc2020

causalinference

python

cef_2017_workshop

Code and teaching material for "Modeling with Julia -- with an Application to the New York Fed DSGE", a workshop at CEF 2017

chapter6

chapter8

class-repo

AEM 7130: Dynamic Optimization/Computational Methods

compecon.jl

Julia versions of the CompEcon routines by Miranda and Fackler.

compecon2020

Computational Economics Course 2020 by Kenneth Judd

compecon_fall17

ECON 815: Computational Methods for Economists

compeconworkshop_2017

competition_io