Comments (2)
The 2018 AEA Continuing Education Webcasts on Machine Learning and Econometrics by Susan Athey and Guido Imbens might be a place to start~
https://www.aeaweb.org/conference/cont-ed/2018-webcasts
from bootcamp2019.
Great reference above to the Susan Athey material. I have taught intro to machine learning for economists every year in the M.A. Program in Computational Economics at the University of Chicago. My most recent Jupyter notebooks are the persp-model-econ_W19/Notebooks/
directory of my modeling course repository. You might just want to fork and clone the whole repo. There are some nice problem sets in this repo. I have listed the machine learning notebooks below with a short description. But I will be updating these notebooks and covering them in the last week of the boot camp. In particular, I will reference some of the content covered by John Rust, Sanjog Misra, and Whitney Newey in the DSE Summer School today and yesterday.
- Classification notebook. This notebook goes through logit, multinomial logit, and K Nearest Neighbors.
- Resampling methods. How to implement the paradigm of cross validation through k-folds and bootstrapping of estimating your model multiple times on training sets and measuring accuracy on test set. This is one of the most important contributions of the machine learning advances in economics, almost as important as the new models.
- Tree-based methods. This notebook goes through decision trees and random forest methods. These end up being powerful machine learning methods that sometimes beat neural nets in accuracy. Also, this notebook introduces the concept of tuning hyperparameters to maximize test set accuracy. This is a powerful concept that is the basis for what TensorFlow is good at.
- Support vector machines. SVM is an important classifier.
- Neural nets. This is an introduction to neural networks. The notebook takes you through the multi-layer perceptron (MLP) model that includes hidden layer (deep nets).
from bootcamp2019.
Related Issues (20)
- How to submit homeworks/problem sets HOT 2
- Rust (1987) Python code
- Sublime Text [or other editor] button in Mac Finder HOT 1
- LaTeX symbols HOT 1
- Errors in running install_SG.sh HOT 5
- Jupyter notebooks on the cluster. HOT 1
- Try grid1.setSurplusRefinement(fTol, -1, "fds")
- Plotting points and function HOT 2
- Fixing the error when running main.py HOT 1
- Midway Alias (an easier way to access Midway, for Mac)
- Draw random numbers in C++ HOT 2
- Does anyone know how to time functions in C on cluster?
- Dynare Pset
- Cannot run Dynare in MatLab HOT 1
- Intertemporal Asset Pricing using scipy.optimize.broyden1 HOT 2
- Bellman equation in Aiyagari problem set HOT 1
- Trouble reading Pickle file & the wayout
- Linear Systems - Sparse matrices HOT 4
- Gauss-Seidel HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from bootcamp2019.