This is an automated email from the ASF dual-hosted git repository.
jxie pushed a commit to branch piiswrong-patch-1-1
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
commit 4903f42bd2a1a069211b04aa9bd219c82eda7472
Author: Eric Junyuan Xie <piiswr...@users.noreply.github.com>
AuthorDate: Tue Nov 21 17:31:11 2017 -0800
Update index.md
---
docs/tutorials/index.md | 9 ++++-----
1 file changed, 4 insertions(+), 5 deletions(-)
diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
index 6429dfb..6432615 100644
--- a/docs/tutorials/index.md
+++ b/docs/tutorials/index.md
@@ -1,14 +1,11 @@
# Tutorials
-These tutorials introduce a few fundamental concepts in deep learning and how
to implement them in _MXNet_. The _Basics_ section contains tutorials on
manipulating arrays, building networks, loading/preprocessing data, etc. The
_Training and Inference_ section talks about implementing Linear Regression,
training a Handwritten digit classifier using MLP and CNN, running inferences
using a pre-trained model, and lastly, efficiently training a large scale image
classifier.
-
-
## Gluon
Gluon is the high-level interface for MXNet. It is more intuitive and easier
to use than the lower level interface.
Gluon supports dynamic (define-by-run) graphs with JIT-compilation to achieve
both flexibility and efficiency.
-This is a selected subset of Gluon tutorials. For the comprehensive tutorial
on Gluon,
-please see [gluon.mxnet.io](http://gluon.mxnet.io).
+
+This is a selected subset of Gluon tutorials that explains basic usage of
Gluon and fundamental concepts in deep learning. For the comprehensive tutorial
on Gluon that covers topics from basic statistics and probability theory to
reinforcement learning and recommender systems, please see
[gluon.mxnet.io](http://gluon.mxnet.io).
### Basics
@@ -32,6 +29,8 @@ please see [gluon.mxnet.io](http://gluon.mxnet.io).
## MXNet
+These tutorials introduce a few fundamental concepts in deep learning and how
to implement them in _MXNet_. The _Basics_ section contains tutorials on
manipulating arrays, building networks, loading/preprocessing data, etc. The
_Training and Inference_ section talks about implementing Linear Regression,
training a Handwritten digit classifier using MLP and CNN, running inferences
using a pre-trained model, and lastly, efficiently training a large scale image
classifier.
+
### Basics
```eval_rst
--
To stop receiving notification emails like this one, please contact
"comm...@mxnet.apache.org" <comm...@mxnet.apache.org>.
