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Friday, May 24, 2019

Aula 23 de Métodos Computacionais em Economia (2019) - Introdução a Aprendizagem de Máquinas

Na nossa vigésima terceira aula de métodos computacionais fizemos uma introdução a aprendizagem de máquinas. Esses são os slides usados em sala.



Soluções de Exercícios


Data: SF salaries

Data: Titanic - ML for Disaster

Data: Forest Cover Type Prediction

Data: Brazilian Cities

Data: Bike Sharing Demand

Data:
Otto Group Product


Data:
Prudentials 1


Data:
Prudentials 2

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Referências

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World - Pedro Domingos

Pattern Recognition and Machine Learning - Christopher Bishop

Deep learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville

The elements of statistical learning - Hastie, Tibshirani e Friedman

Modern multivariate statistical techniques - Alan Julian Izenman

The discipline of machine learning - T. M. Mitchel

A few useful things to know about machine learning - P. Domingos

Learning deep architectures for AI - Y. Bengio

In defence of forensic social science - Amir Goldberg [Big data and Society, 2015]

Sociology in the era of big data: the ascent of forensic social science - D. A. McFarland e
K. Lewis [American Sociology, 2015]

Economic reason and artificial intelligence - D. C. Parkes and M. P. Wellman [Sience 349,
p.267, 2015]

Big Data: New Tricks for Econometrics - H. R. Varian

The Impact of Machine Learning on Economics - Susan Athey

The State of Applied Econometrics: Causality and Policy Evaluation
Susan Athey e Guido W. Imbens.

Beyond Prediction: Using Big Data for Policy Problems -
Susan Athey

High-Dimensional Methods and Inference on Treatment and Structural Effects in Economics - Victor Chernozhukov, A. Belloni and C. Hansen

Prediction Policy Problems -
Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, and Ziad Obermeyer