Resources

Some of my favorite things

references

simple guide to github

the essentials

style guide for python code

this is an extensive style guide, find the key points here.

getting started with data science

data literacy and training from data carpentry

–> atmosphere and ocean lessons
domain specific data workshops, including python for atmosphere and ocean netCDF files

getting started with Bayesian statistics

My personal curriculum for learning Bayesian statistics as someone with extensive math but light stats training.

  1. Bayesian Statistics: From Concept to Data Analysis

  2. Bayesian Statistics: Techniques and Models

  3. Probabilistic Programming & Bayesian Methods for Hackers


on my github

Winning Hackathon Submission & Geospatial Tutorial

The code for a winning submission to the SPARK+AI Summit 2020 Hackathon for Social Good. The same data is used in a tutorial for getting started with geospatial data in Python (see folder “WiDS Tutorial” for presentation and accompanying notebook)

machine learning exercises

my solutions for the exercises in Andrew Ng’s Coursera Machine Learning class translated to python. Exercises 1-4 are available for now, I will possibly resume this later on.

machine learning for an estuarine water quality dataset

I started adapting the exercises above to data from the Chesapeake Bay Program water quality dataset. Only one exercise for now, possibly more to come.