I usually have a lot of trouble sleeping and was panicking after I read the book. The side effects of not sleeping did seem kind of exaggerated, but glad to know someone actually took the time to corroborate all the claims.
Pedantry note: corroborate claims is exactly what this article did not do. Maybe you had a thinko or left out a word, I certainly that from time to time, but alternately maybe you want to look up what the fancy word means.
HTH
(Maybe you're just sleep deprived! (I kid, I kid))
Yes I write letters to my future self once in a while, maybe a year or two into the future. It's really interesting to read what my life was like when I wrote the letter and I'm always curious if things turned out as expected and if I managed to achieve some of my goals.
Interesting article. I thought I was an assessment-oriented decision maker since I often get paralyzed when I'm faced with life changing decisions. But the assessment placed me closer to the locomotion-oriented.
I guess it would be helpful to know how one can work on making better assessment-oriented decisions?
I wish I'd read up about the stability of the company I'm joining and if they're financially sound or not. Companies that aren't doing well financially usually have problems with management (for example, projects don't get enough funding).
Another thing I missed is if the people on your team sound bored or don't seem interested or excited about their work. One way I found telling was if they didn't go into details about their projects and try to be ambiguous.
Thank you. I actually didn’t base it on fast.ai. It went on like so:
- I scraped from google images using queries like “ripe bananas”, “green bananas”, etc
- Filtered out garbage images and labeled the remaining with the help of someone
- Trained the model (very straight forward with Keras). The code in the notebook is something like 30 lines I think.
- Using tf.js was what took me the longest. Using tensorflowjs_converter.save_model outputs an incompatible or corrupted file. Saving it first with keras and then using the tensorflowjs_converter CLI tool is what worked. The web-ui code is also available in the repo.
- Lastly. It is served from GitHub pages (not a problem since everything is static and runs client side), with a custom freenom domain (on a convenient .ml tld) and through cloudflare’s DNS which gives me SSL on a custom domain, caching and some very basic analytics.
Everything free tier. It only cost me time (around 5h I think).
