written by Eric J. Ma on 2020-01-02 | tags: data science statistics automation bayesian
How automated statistical procedures can still be useful.
Read on... (416 words, approximately 3 minutes reading time)written by Eric J. Ma on 2019-12-26 | tags: data science dashboarding python
How one can serve up multiple panel apps on the same Panel server.
written by Eric J. Ma on 2019-12-19 | tags: bayesian data science uncertainty decision making
Some reflections on uncertainty after reading a blog post by Brandon Rohrer.
Read on... (342 words, approximately 2 minutes reading time)written by Eric J. Ma on 2019-12-15 | tags: dashboarding python data science data visualization software development
My reflection on the Python dashboarding landscape. There's been a lot of activity, and I provide some recommendations on how we as data scientists can choose between tools.
Read on... (1617 words, approximately 9 minutes reading time)written by Eric J. Ma on 2019-11-09 | tags: data science git workflow
A short synopsis of a recent essay I wrote, on how to use GitFlow in data science projects.
Read on... (160 words, approximately 1 minute reading time)written by Eric J. Ma on 2019-10-31 | tags: data science deep learning testing pair programming code review
I share my thoughts on why re-implementing deep learning models from scratch can be a very valuable activity.
Read on... (1585 words, approximately 8 minutes reading time)written by Eric J. Ma on 2019-10-30 | tags: essays data science workflow good practices
My thoughts on how to do code review in data science projects effectively.
Read on... (586 words, approximately 3 minutes reading time)written by Eric J. Ma on 2019-10-29 | tags: data science drug development artificial intelligence medicine
A mini-rant on why I think hyped-up "AI" has a very long way to go, and that medicine is much too complex for us to solve at one shot.
Read on... (530 words, approximately 3 minutes reading time)written by Eric J. Ma on 2019-10-18 | tags: python tips optimization packages
cachier, a really nifty tool for caching function results, is really useful and easy-to-use! Come read why.
written by Eric J. Ma on 2019-10-05 | tags: jupyter dataops devops data science
Some notes on how to serve up an HTTPS-enabled Jupyter server.
Read on... (410 words, approximately 3 minutes reading time)