escanor

6 ms·

1. 1.▲
   by escanor 3mo ago

   brilliant!
2. 2.▲
   by escanor 3mo ago

   it is: (async function(oracle, punch, delay) { async function sleep(ms) { return new Promise((resolve, _) => { setTimeout(resolve, ms) }) } for (let i = 0; i < 100; i++) { const state = o
3. 3.▲
   by escanor 3mo ago

   pure random player: (async function(punch, delay) { async function sleep(ms) { return new Promise((resolve, _) => { setTimeout(resolve, ms) }) } for (let i = 0; i < 100; i++) { punch([&#x
4. 4.▲
   by escanor 3y ago

   Who does that algorithm really serve?
5. 5.▲
   by escanor 4y ago

   great work! just a note regarding tf-idf, when you mention log10: i think you're missing the point on the reason of log and most importantly base 10. namely, using log10 gives us a perspective on the number of digits of the term/d
6. 6.▲
   by escanor 5y ago

   > for index, item in enumerate(menu): should be > for index, item in enumerate(menu, start=1): for the example to be correct :)
7. 7.▲
   by escanor 5y ago

   yes, i see this as well. at first it was confusing, but later i understood it was the output.
8. 8.▲
   by escanor 7y ago

   My understanding is that the neural network is used to predict the "magnitude" of each eigenvector/axe (extracted by using PCA) in order to reconstruct an approximation of the original behavior.