Eric J Ma's Website

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PyCon 2019 Sprints

written by Eric J. Ma on 2019-05-11 | tags: pycon software development sprint open source

Together with my colleague Zach Barry, we led a pyjanitor sprint! It was really fun, looking forward to more in the future!

Read on... (1892 words, approximately 10 minutes reading time)
Context Switching

written by Eric J. Ma on 2019-05-10 | tags: programming coding data science

Some realizations on how disruptive context switching can be. My first thoughts on how to deal with it during a sprint...

Read on... (240 words, approximately 2 minutes reading time)
PyCon 2019 Tutorial and Conference Days

written by Eric J. Ma on 2019-05-10 | tags: pycon 2019 conferences data science

My real-time thoughts on SciPy 2019’s tutorial and conference days. It’s been a pretty awesome experience thus far, though shouldering three tutorials was indeed a marathon for me, much as I love teaching!

Read on... (383 words, approximately 2 minutes reading time)
PyCon 2019 Pre-Journey

written by Eric J. Ma on 2019-04-29 | tags: pycon python data science conferences

I'm headed out to PyCon 2019! This year, I will be co-instructing two tutorials, one on network analysis and one on Bayesian statistics, and delivering one talk on Bayesian statistics.

The first... (read more)

(329 words, approximately 2 minutes reading time)
Variance Explained

written by Eric J. Ma on 2019-03-24 | tags: data science machine learning

Have you heard of variance explained as a loss function and machine learning metric? Turns out it’s quite useful and interpretable. I’d like to share this new learning with you.

Read on... (440 words, approximately 3 minutes reading time)
Functools Partial

written by Eric J. Ma on 2019-03-22 | tags: python hacks tips and tricks data science productivity coding

In praise of functools.partial, and how I used it in a Flask/Bokeh app!

Read on... (415 words, approximately 3 minutes reading time)
How I Work

written by Eric J. Ma on 2019-03-20 | tags: data science productivity

My tooling, routines, and techniques for getting things done and learning new things!

Read on... (825 words, approximately 5 minutes reading time)
Pair Coding: Why and How for Data Scientists

written by Eric J. Ma on 2019-03-01 | tags: data science programming best practices

In this Q&A-style blog post, I detail how data scientists can begin to engage in pair coding as a more common practice in our day-to-day work, and why we should spend the time to do it as much as we can afford.

Read on... (840 words, approximately 5 minutes reading time)
Minimum Viable Products (MVPs) Matter

written by Eric J. Ma on 2019-01-28 | tags: data science data products minimum viable products

I would like to encourage you to build more "minimum viable products" of your projects. Come learn why they’re so valuable!

Read on... (100 words, approximately 1 minute reading time)
ADVI: Scalable Bayesian Inference

written by Eric J. Ma on 2019-01-21 | tags: scalability bayesian model dose response parameter learning model specification convergence shrinkage large dataset nuts mcmc advi variational inference neural networks random sampling biochemistry data modeling

I've been exploring a Bayesian hierarchical 4-parameter dose response model at work. Initially, I used a few thousand samples for prototyping, but I've now scaled up to 400K+ samples. Fitting the model with NUTS would've taken a week, but ADVI did the job in just 2.5 hours. 🚀 This experience has given me a new appreciation for ADVI, even in simpler models with large datasets. 🧠

Read on... (365 words, approximately 2 minutes reading time)
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