Giter Club home page Giter Club logo

columbia_mini_course's Introduction

Computational Economics with Python

Graduate Mini Course at Columbia University

  • Instructor: John Stachurski
  • Dates: 26--28th March 2018
  • Times and location: see here

Summary

This mini course will provide a fast paced introduction to Python for computational economic modeling, from basic scripting to high performance computing. The course is aimed at graduate students with proficiency in at least one scientific computing platform (e.g, MATLAB, Fortran, STATA, R, C or Julia).

No Python knowledge is assumed.

Please be sure to bring your laptop

Instructions

Get Python + scientific libraries

Update Numba (still necessary as of 25th March 2018)

  • At terminal (Mac / Linux) or Anaconda Prompt (Windows), type conda install numba=0.37

Get files from this repo

Schedule

Day 1

  • Python vs MATLAB vs Julia vs Fortran vs others
  • The Python language: syntax and semantics
  • Object oriented vs procedural programming
  • Jupyter notebooks

Day 2

  • The major scientific libraries ( SciPy / NumPy / Matplotlib / etc.)
  • Numba and other JIT compilers
  • Parallelization
  • Distributed and cloud computing

Day 3

  • Applications (asset pricing, optimal savings, optimal stopping)

Links:

Notes on AWS

To get an instance running

  1. Login to Amazon AWS Console
  2. Navigate to EC2 Service
  3. Choose your region for setting up an instance
  4. Create security key-pair for the region if you don't have one
  5. Launch & Configure an instance and choose Ubuntu 64-bit
  6. enable access through Port 8000 (in addition to Port 22 for ssh)
  7. Choose security key you've set up

Connecting and set up

Use ssh -i /path/to/pem-key ubuntu@hostname

Here hostname is your Public DNS, as shown in the instance information from AWS console

Now run sudo apt-get update so you can install things you might need using apt-get

Configure instance to run Jupyter

  1. ssh into the running instance using IP from AWS Console
  2. Install Anaconda using wget and the latest download link for python36
  3. Run: jupyter notebook --generate-config
  4. For Automatic Password Setup run: jupyter notebook password
  5. Edit .jupyter/jupyter_notebook_config.py and set the following
# Set ip to '*' to bind on all interfaces (ips) for the public server
c.NotebookApp.ip = '*'
c.NotebookApp.open_browser = False
c.NotebookApp.port = 8000

columbia_mini_course's People

Contributors

jstac avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.