From 276715fa821c09f067efc34e2017e88b5c5f4b7c Mon Sep 17 00:00:00 2001 From: wassname Date: Sat, 18 Nov 2017 08:46:31 +0800 Subject: [PATCH] readme --- readme.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/readme.md b/readme.md index 2b74282..9063bd6 100644 --- a/readme.md +++ b/readme.md @@ -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.