Talks and presentations

Mixed Effects Regression

September 26, 2018

Talk, R-Ladies, Seattle, WA

The combination of power, flexibility and clearly interpretable models make it a very powerful technique. I’ll introduce you to the method (no stats background required!), show you how to apply it to your own datasets and walk you through some tricks for clearly visualizing the output.

Data Science Portfolios

September 19, 2018

Talk, R-Ladies, Washington, DC

This talk describes how to put together a data science portfolio that will help you stand out, different kinds of data science jobs and how to tailor your application to shine as a candidate.

I do, We do, You Do: Supporting active learning with notebooks

August 22, 2018

Workshop, JupyterCon, New York NY

The gradual release of responsibility instructional model (also known as the I do, We do, You do model) is a pedagogical technique developed by Pearson & Gallagher where students engage with material more independently over time. In this workshop, participants will learn how to apply the I do, We do, You do framework to teaching with Jupyter notebooks. Over the course of the workshop, participants will complete a series of exercises designed to help them use Jupyter notebooks more effectively support active learning in the classroom.

Reproducible Research Best Practices (highlighting Kaggle Kernels)

August 21, 2018

Workshop, JupyterCon, New York NY

In this workshop, we’ll take an existing research project and make it fully reproducible using Kaggle Kernels. This workshop will include hands-on instruction and best practices for each of the three components necessary for completely reproducible research.

Evaluating and Improving Reproducibility in Machine Learning

August 08, 2018

Talk, Puget Sound Programming Python (PuPPy), Seattle, WA

Reproducibility in machine learning means you can run the same code on the same data and get the same results. While this may seem relatively straightforward, there are plenty of potential pitfalls. In this talk, we’ll discuss a scale for evaluating the reproduciblity of a machine learning project and how to make sure that your own work is easy to reproduce. While this talk is focused on researchers (it’s based on a paper I presented at an ICML workshop), the tips and tricks should apply to anyone who does exploratory data analysis or machine learning generally.

How to Give a Lightning Talk

March 19, 2018

Talk, R-Ladies Seattle, Chicago IL

Lightening talks are quick talks, usually under 5 minutes. The short format makes the great for first time speakers! This is a very meta lightening talk on how to give a lightening talk, and covers how to develop your talk, practice it and some of my best public-speaking tips.

How to find stories in data through visualization

March 09, 2018

Talk, The National Institute for Computer-Assisted Reporting, Chicago IL

Working with data is a kind of interview - it is a complex back-and-forth, drawing out the expressiveness of data. The process is often visual, depending heavily on a sequence of graphical displays, “visualizations.” This three-hour workshop will focus on the concepts and skills you need to use data visualization effectively as part of your reporting practice - to conduct a data interview. You will learn how to spot trends, highlight changes over time, identify outliers, make meaningful comparisons, and describe important patterns in your data - all through the effective use of visualization strategies. This class will be based in the R language and distributed through Jupyter notebooks. These pre-built examples can later be customized to suit your own projects when you return to your newsroom.

Socially-Stratified Validation for ML Fairness

February 13, 2018

Talk, Women in Data Science, Seattle, WA

In this talk, I cover some of the frameworks used to think about fairness in machine learning. Then I turn to more practical matters of determining which social factors are important in machine leaning, how to find appropriate validation data, and considerations when selecting metrics. Finally, I walk through a sample socially-stratified validation pipeline.

Character Encoding and You�

January 23, 2018

Talk, PyCascades, Vancouver BC

Why does your text output have all those black boxes in it? Why can’t it handle Portuguese? The answer is most likely “character encoding”. This talk will cover some of the common character encoding gotchas and cover some defensive programming practices to help your code handle multiple encodings.

Intro to Kaggle: XGBoost!

January 16, 2018

Talk, Metis, Seattle WA

This workshop was both an introduction to Kaggle and a beginner-friendly workshop on XGBoost algorithm. You’ll need to provide some info to watch the video, but the same content is covered in the code.

Why does NLP need sociolinguistics?

September 25, 2017

Talk, Women Tech Makers Seattle, Seattle WA

This talks covers the basics of sociolinguisitics and discusses why it’s important to considering linguistic variation when designing NLP applications.