written by Eric J. Ma on 2018-07-26 | tags: scipy conferences python
It's been about two weeks since SciPy 2018 ended, and I've finally found some breathing room to write about it.
SciPy 2018 is the 4th year I've made it to the conference, my first one being SciPy 2015 (not 2014, as I had originally... (read more)
(576 words, approximately 3 minutes reading time)written by Eric J. Ma on 2018-07-16 | tags: bayesian statistics data science
Over the past year, having learned about Bayesian inference methods, I finally see how estimation, group comparison, and model checking build upon each other into this really elegant framework for data analysis.
written by Eric J. Ma on 2018-07-14 | tags: statistics visualization data science
I detail why ECDFs are superior to histograms as a way of visualizing distributions. In short, they provide richer information than histograms do. Come learn about them!
Read on... (611 words, approximately 4 minutes reading time)written by Eric J. Ma on 2018-06-17 | tags: git version control code snippets
I learned a new thing this weekend: we apparently can apply a patch onto a branch/fork using git apply [patchfile].
There's a few things to unpack here. First off, what's a patchfile?
The long story cut short... (read more)
(729 words, approximately 4 minutes reading time)written by Eric J. Ma on 2018-06-05 | tags: data science machine learning deep learning causal inference graph theory probability
It took reading Judea Pearl's "The Book of Why", and Jonas Peters' mini-course on causality, for me to finally figure out why I had this lingering dissatisfaction with modern machine learning. It's because modern machine learning (deep... (read more)
(662 words, approximately 4 minutes reading time)written by Eric J. Ma on 2018-05-26 | tags: causal inference
Finally, I have finished Judea Pearl's latest work "The Book of Why"! Having read it, I have come to appreciate... (read more)
(208 words, approximately 2 minutes reading time)written by Eric J. Ma on 2018-05-06 | tags: machine learning data science deep learning automl
For any problem that we think is machine learnable, having a sane baseline is really important. It is even more important to establish them early.
Today at ODSC, I had a chance to meet both Andreas Mueller and Randy Olson. Andreas leads
written by Eric J. Ma on 2018-03-30 | tags: programming code snippets scripting python data science
click is amazing! It's a Python package that allows us to add a command-line interface (CLI) to our Python scripts easily. This blog post is a data scientist-oriented post on how we can use click to build...
(read more)
written by Eric J. Ma on 2018-02-28 | tags: data science deep learning message passing neural networks software engineering graph theory
At work, I’ve been rolling my own deep learning package to experiment with graph convolutional neural networks. I did this because in graph-centric deep learning, an idea I picked up from this paper, the inputs, convolution kernels, and much more,... (read more)
(657 words, approximately 4 minutes reading time)written by Eric J. Ma on 2018-02-26 | tags: teaching education datacamp
It always brings me joy to see others benefit from what I can offer.
Thanks for sharing the fruits of your journey on LinkedIn, Umar!
Also a big... (read more)
(103 words, approximately 1 minute reading time)