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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

1806

18.06 course at MIT

30-seconds-of-python

Short Python code snippets for all your development needs

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

advancedmethodsdataanalysisclass

analisisestadisticor

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

approachingalmost

Approaching (Almost) Any Machine Learning Problem

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

awesome-economics

A curated collection of links for economists

bayesian_analisys

Ejercicio practico del taller de Rstan

book-networks

Companion Site for Economic Networks: Theory and Computation

bootcamp2019

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

c-in-a-nutshell-2e

cge

This is an R package for developing CGE models, computing general equilibrium and simulating economic dynamics with structural dynamic models in LI (2019) "General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. Beijing: Economic Science Press".

cheatsheets

RStudio Cheat Sheets

climate-econ

Tracking literature in climate/environmental/ecological economics

coding-interview-university

A complete computer science study plan to become a software engineer.

columbia-mm-notebooks

comandos-git

Lista de los comandos mas utilizados en git y la terminal

compecon

My "Foundations of Computational Economics" course

compecon-1

CompEcon is a set of MATLAB functions for solving a variety of problems in economics and finance. The library functions include rootfinding and optimization solvers, a integrated set of routines for function approximation using polynomial, splines and other functional families, a set of numerical integration routines for general functions and for common probability distributions, general solvers for Ordinary Differential Equations (both initial and boundary value problems), routines for solving discrete and continuous time dynamic programming problems, and a general solver for financial derivatives (bonds, futures, options).

compecon2020

Computational Economics Course 2020 by Kenneth Judd

computational-methods-in-macro

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

computationalmethodsclass

Class Materials for 47-809 Computational Methods for Economics at Carnegie Mellon

consumer_theory_choice_experiment_game

Using Discrete Choice Experiments as a Tool for Teaching Consumer Theory: Intermediate Microeconomics

cornell-cs5785-2020-applied-ml

Teaching materials for the applied machine learning course at Cornell Tech (online edition)

crm

curso-see

Taller Final del curso: Procesamiento de Lenguaje Natural organizado por la Sociedad Ecuatoriana de Estadística, dictado por Hugo Porras

curso_r_eph_clases

Curso de R para procesamiento de datos de la Encuesta Permanente de Hogares