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... (1612 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... (1571 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... (580 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)written by Eric J. Ma on 2019-10-05 | tags: teaching bayesian statistics
Do we use multiple examples to highlight the same point, or do we take one example and layer on complexity? It all depends.
Read on... (187 words, approximately 1 minute reading time)written by Eric J. Ma on 2019-09-07 | tags: data apps data science devops deployment
Some of the benefits of using Dokku as a PaaS solution for data scientists. It's free, open source, and when paired with the right tools, enables data scientists to focus on making their data app prototypes.
Read on... (779 words, approximately 4 minutes reading time)written by Eric J. Ma on 2019-07-29 | tags: software development sprint code sprint open source community community development
Post-PyCon, I detail some of my thoughts on how one can productively participate in a code sprint as a participant.
Read on... (852 words, approximately 5 minutes reading time)