My “throw wet toliet paper at the wall” first try at ML!
I briefly looked at the Fast.AI course last year, real life got in the way, but now I’m back. Going to actually finish it this time.
So I got my Paperspace account running, ran through the first lesson notebook, watched the video, made my own notes etc. Challenged myself to make my own classifier with my own data.
The simplest and quickest thing I could think of was to use the ‘People’ feature in iPhotos to select pictures of my family. I just trusted Apple’s deep learning was correct, (it isn’t) exported the files, made a tar file, then used the ‘Upload’ button on my noteboook. This took about 3 hours with a 330Mb file, so if anyone knows a better way…
I duplicated the lesson 1 book again, then deleted some of the notes
The results are hopeless, as expected, although better than chance, ( a 0.66 error rate?) with a rate of 0.44 ish
It all seemed pretty straightforward really. Fun if not particularly useful.
Even this daft example seems to be able to recognize my daughter apart from her parents. I won’t be submitting this to Kaggle anytime soon, I found it help me understand what was going on much better than just watching the video and clicker Shift-Enter a few times