Aug 14

AWS, AWS, and More AWS

It’s been a summer of AWS for me.

Jul 19

To Optimize, or Not?

You should be forced to write efficient code and know how to do it in situations where it matters. You should also be able to recognize when it’s more important to optimize for readability, maintainability and clarity.

Mar 21

michaelgat

The horrors of open source!

It’s possible to simplify the “normal” things for normal users while still providing source code and repositories that allow us strange creatures to continue experimenting, testing, and yes, struggling with inevitable incompatibilities all night long.

Feb 24

michaelgat

Catching up

2018 is looking busy, but there’s still a lot left from 2017 that I didn’t write about or wrap up.

Jul 10

michaelgat

Udacity Deep Learning Nanodegree — Part 3

I found TensorFlow initially confusing but then quite comfortable. It’s odd how after programming in a language like Python for a while, it becomes confusing that you have to declare “placeholders” (variables) and constants up-front, then initialize them.

Jun 26

michaelgat

Udacity Deep Learning Nanodegree – Part II

I left last week’s PyData Meetup with more questions than answers. Questions like “why does that neural net I just wrote perform the way it does?” So, with a couple of weeks left until the next project is due, I decided to go back and revisit the second half of the neural networks topic before moving forward.

Jun 22

michaelgat

PyData Socal: Explaining Black Box ML Predictions

Tonight I joined the first Southern California PyData meetup. It featured two speakers discussing how to better understand the predictions made by machine-learning models, and why it might be important to do so. I was impressed by the capabilities of the packages demonstrated and the likely importance of having such capabilities as we move forward with deep learning-based automation that could cause catastrophic results if it fails in unexpected ways.