From ad82417a24fec143fca6ea9a71a90540a1a14cc4 Mon Sep 17 00:00:00 2001
From: autodocs
-Flux is a machine learning library, implemented in Julia. In a nutshell, it simply lets you run normal Julia code on a backend like TensorFlow. It also provides many conveniences for doing deep learning. +Flux is a library for machine learning, implemented in Julia. In a nutshell, it simply lets you run normal Julia code on a backend like TensorFlow. It also provides many conveniences for doing deep learning.
-This gives you great flexibility. You can use a convenient Keras-like API if you want something simple, but you can also drop down to straight mathematics, or build your own abstractions. You can even use Flux's utilities (like optimisers) with a completely different backend (like
+Flux is very flexible. You can use a convenient Keras-like API if you want something simple, but you can also drop down to straight mathematics, or build your own abstractions. You can even use Flux's utilities (like optimisers) with a completely different backend (like
Knet
diff --git a/latest/internals.html b/latest/internals.html
index 3851d056..a233ed71 100644
--- a/latest/internals.html
+++ b/latest/internals.html
@@ -136,7 +136,7 @@ Internals
-
+
diff --git a/latest/models/basics.html b/latest/models/basics.html
index 86d8914b..b5b48d78 100644
--- a/latest/models/basics.html
+++ b/latest/models/basics.html
@@ -170,7 +170,7 @@ Model Building Basics
-
+
@@ -347,7 +347,7 @@ Dressed like a model
We noted above that a model is a function with trainable parameters. Normal functions like
exp
- are actually models too, that happen to have 0 parameters. Flux doesn't care, and anywhere that you use one, you can use the other. For example,
+ are actually models too – they just happen to have 0 parameters. Flux doesn't care, and anywhere that you use one, you can use the other. For example,
Chain
will happily work with regular functions: