What model?

DeepLens is a hobby IoT device Amazon sells.  It is a small Intel-Atom powered computer (2 cores, 1.3 GHz) with a camera builtin.

I have the 1.0 version.  There is a 1.1 version that is faster, and I can see why they made that!

My version is painfully slow to use.

My original idea (just over four years ago) was to set it up and then SSH into it and poke at it from time-to-time.

But ... it's really good to have a screen so you can see what the camera is seeing!

(There is no doubt a way to do this remotely but I didn't figure it out.)

Well, I powered it up today, with the goal of doing a factory reset.  The instructions are long and complicated, basically resulting in a 16 GB USB stick that it will boot from and erase itself.  And I made it harder by doing it on the device itself!

I learned stuff about Linux file systems.  That's good.

When I was done I had evolved my setup quite a bit, from just the device plugged into an HDMI monitor and keyboard and mouse, to lots of additional power and a USB-extender.

Frankensetup for factory reset!

Luckily the Seahawks made it to the playoffs today (sadly, they failed on their quest, but dang, what a successful first half!).  So when I started up long-running operations on DeepLens I was actually busy watching American football.

Picture copied from AWS site.  Should be linked.

I remember four years ago I followed the instructions, registered the device to an AWS account, got all the IAM settings correct, and then started to follow the tutorial for doing some machine learning.

Then I hit the showstopper: "Pick your model."

What model is that?  For what?  Don't I just give it a bunch of pictures and train it?  You mean I have to understand what a model is!  Well, I don't.

Yesterday, I used a Google service to translate some speech to text.  It said, "Pick your model", but luckily it had a dropdown, so I just picked one.  

Pick your model.  Isn't that a huge part of being a data scientist who specializes in machine learning?  Knowing the strengths and weaknesses of models?

I dunno.  Someday I'll learn what a model is, and how that is different from the data.  Or I'll learn something completely different because I don't understand any of these terms at all.

It's on my list of things to learn about, this mysterious machine learning, that as I write this is generating art, text, and even computer code.

But not right now.