Updated minor changes

Co-authored-by: Michael Abbott <32575566+mcabbott@users.noreply.github.com>

Author: vivekkumar7089

src/layers/conv.jl

@@ -42,7 +42,7 @@ and a batch of 50 would be a `100×100×3×50` array.
 This has `N=2` spatial dimensions, and needs a kernel size like `(5,5)`,
 a 2-tuple of integers.
 
-To take convolutions along `N` dimensions, this layer expects as input an array
+To take convolutions along `N` feature dimensions, this layer expects as input an array
 with `ndims(x) == N+2`, where `size(x, N+1) == in` is the number of input channels,
 and `size(x, ndims(x))` is (as always) the number of observations in a batch.
 Then: