chinaperrin / ssa_machine_learning_2019

Machine Learning Workshop at SSA 2019

Introduction

This folder will contain the material for the machine learning workshop for SSA 2019.

Structure of the repo

The folder is structured as:

• notebooks - folder contains all the Jupyter notebooks
• data - folder contains data used for examples
• figs - folder contains images used in the notebooks
• presentations - folder contains the presentation slides

Note that this workshop aims to give you a sense of how machine learning works using Python and seismological examples. We assume you have basic working knowledge of Python. All the dependencies are listed in the environment.yml file with the versions specified. If you want to install the packages and run a local version on your own machine, the easiest way is to use Anaconda or miniconda, and use either conda or pip to install all the dependencies.

Content of the workshop

In this workshop, we will cover:

• Introduction of machine learning (Karianne)
• Clustering (Daniel)
• Feature selection and engineering (Maruti)
• Classification (Qingkai)
• Regression (Zefeng)
• Deep learning (Youzuo)

Running the code

If you just want to run the code in the cloud, press the 'launch Binder' badge on the top left corner of the page.

Currently it contains un-finished work, use at your own risk. It will be fully ready before April 23rd.

Instructors:

(alphabetical order)

• Karianne J. Bergen
• Qingkai Kong
• Zefeng Li
• Youzuo Lin
• Maruti K. Mudunuru
• Daniel T. Trugman