readme

2026-09-11 12:30:31 +08:00 · 2017-11-18 08:46:31 +08:00
parent f13ce1c42c
commit 276715fa82
1 changed files with 2 additions and 0 deletions
@@ -2,6 +2,8 @@ MNIST is the hello world of machine learning. When we learn our optimizer is mov

 To do this we map mnist as we vary two nuerons. We reduce mnist to a binary problem (is the number less than 5), and reduce the dimensionality with a single conv2d layer. There are no hidden layers, and the head is a dense layer with two neurons: nueron x and nueron y. For our z axis we use loss.

+The result is quite smooth and covex, but perhaps that's a result of how I set up the problem.
+
 Steps:
 - Pre-train a model
 - freeze all but the x and y neurons parameters.