Soluções de Exercícios
1. Problema de machine learning
Data: Adult Salary predictor do Kaggle
Data: Restaurant Revenue Prediction" do Kaggle
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
Kaggle: House Rent Prediction Datase
Kaggle: Medical Cost Personal Dataset
.
Kaggle: Diamonds - Analyze diamonds by their cut, color, clarity, price, and other attributes
Kaggle Restaurant Revenue Prediction
Kaggle: Credit Score Classification Dataset
Worldwide deaths by country/risk factors" do Kaggle
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
