I mentioned three lines of effort yesterday, but I didn't come up with a plan for achieving them. So, here's my plan:
A while ago, I bought the LPC810 kit, but I need to find it. After about a half hour of rummaging through my parts bins I wasn't able to find it. The nice thing about it was that it was easy to program, at least with the embello libraries. So with that in mind, I'll look at his templates for programming the bluepill and maybe approach it the same way.
- Look for LPC-810 again.
- Look at template for STM32: can I do it without a bunch of complications?
- Failing that, look to see if one of the M0 Feathers can be used similarly.
- Set up breadboard for appropriate platform.
I should be able to get through the first chapter by the end of August. It seems like a long ways away, but I want to work through more of the exercises and programming drills, and it will account for starting a new job.
- Get through Hilbert spaces (i.e. finish two sections) by the end of the week.
I'm anxious to get to the part where I can start playing around with the Rigetti API and the MSQDK, but I need to get through the foundations. Slow but steady. I should also make some Anki flashcards for this.
The programming drills I still need to do:
- Programming drill 2.1.1: Write three functions that perform addition, inverse, and scalar multiplication operations for Cn, i.e. write a function that accepts the appropriate input for each of the operations and outputs the vector.
- Programming drill 2.2.1: Convert your functions from the last programming drill so that instead of accepting elements of Cn, they accept elements of Cm×n.
- Programming drill 2.2.2: Write a function that accepts two complex matrices of the appropriate size. The function should do matrix multiplication and return the result.
- Programming drill 2.2.3: Write a function that accepts a vector and a matrix and outputs the vector resulting from the action.
I currently have some code in C++, but I might switch to Go just to remember how to write it again.
Math for Machine Learning
JFDI: make sure to do the videos and exercises on time.