Feeling pretty good about lesson 1. Here is recap about what I did.
- Finished watching the lesson
- Set up my environment (script crashed when installing anaconda but I was able to hack at it till it worked)
- Made my own breakfast dataset (frenchtoast, pancakes, and waffles)
- Tried to re-create notebook from memory to make an image classifier for my breakfast dataset. I ended up copying a lot of the lesson’s code but I typed it myself. Copying by typing out the code was where I learned most during the lesson.
- Found a useful forum post about multi class probabilities and a new class for visualize image model results.
Here are links:
breakfast ipynb. Pictures at the end are pretty interesting. I really surprised that some of the pancakes were not classified correctly. I was also unable to get the Cyclical Learning Rates to work. I think this might be because of a lack of images (50 train, 50 validation of each category) - but any advice here is appreciated.