diff --git a/README.md b/README.md index 04b7bcf9e7fa..8db55af4ff87 100644 --- a/README.md +++ b/README.md @@ -28,14 +28,14 @@ Apache MXNet (incubating) for Deep Learning ![banner](https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/banner.png) Apache MXNet (incubating) is a deep learning framework designed for both *efficiency* and *flexibility*. -It allows you to ***mix*** [symbolic and imperative programming](https://mxnet.incubator.apache.org/architecture/index.html#deep-learning-system-design-concepts) +It allows you to ***mix*** [symbolic and imperative programming](https://mxnet.incubator.apache.org/api/architecture/program_model) to ***maximize*** efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. MXNet is more than a deep learning project. It is a collection of -[blue prints and guidelines](https://mxnet.incubator.apache.org/architecture/index.html#deep-learning-system-design-concepts) for building +[blue prints and guidelines](https://mxnet.incubator.apache.org/api/architecture/overview) for building deep learning systems, and interesting insights of DL systems for hackers. Ask Questions @@ -71,24 +71,21 @@ What's New * [MKLDNN for Faster CPU Performance](./docs/tutorials/mkldnn/MKLDNN_README.md) * [MXNet Memory Monger, Training Deeper Nets with Sublinear Memory Cost](https://github.com/dmlc/mxnet-memonger) * [Tutorial for NVidia GTC 2016](https://github.com/dmlc/mxnet-gtc-tutorial) -* [Embedding Torch layers and functions in MXNet](https://mxnet.incubator.apache.org/faq/torch.html) -* [MXNet.js: Javascript Package for Deep Learning in Browser (without server) -](https://github.com/dmlc/mxnet.js/) -* [Design Note: Design Efficient Deep Learning Data Loading Module](https://mxnet.incubator.apache.org/architecture/note_data_loading.html) -* [MXNet on Mobile Device](https://mxnet.incubator.apache.org/faq/smart_device.html) -* [Distributed Training](https://mxnet.incubator.apache.org/faq/multi_devices.html) -* [Guide to Creating New Operators (Layers)](https://mxnet.incubator.apache.org/faq/new_op.html) +* [MXNet.js: Javascript Package for Deep Learning in Browser (without server)](https://github.com/dmlc/mxnet.js/) +* [Guide to Creating New Operators (Layers)](https://mxnet.incubator.apache.org/api/faq/new_op) * [Go binding for inference](https://github.com/songtianyi/go-mxnet-predictor) * [Amalgamation and Go Binding for Predictors](https://github.com/jdeng/gomxnet/) - Outdated * [Large Scale Image Classification](https://github.com/apache/incubator-mxnet/tree/master/example/image-classification) Contents -------- -* [Documentation](https://mxnet.incubator.apache.org/) and [Tutorials](https://mxnet.incubator.apache.org/tutorials/) -* [Design Notes](https://mxnet.incubator.apache.org/architecture/index.html) +* [Website](https://mxnet.incubator.apache.org) +* [Documentation](https://mxnet.incubator.apache.org/api) +* [Blog](https://mxnet.incubator.apache.org/blog) * [Code Examples](https://github.com/apache/incubator-mxnet/tree/master/example) -* [Installation](https://mxnet.incubator.apache.org/install/index.html) -* [Pretrained Models](http://mxnet.incubator.apache.org/api/python/gluon/model_zoo.html) +* [Installation](https://mxnet.incubator.apache.org/get_started) +* [Features](https://mxnet.incubator.apache.org/features) +* [Ecosystem](https://mxnet.incubator.apache.org/ecosystem) Features -------- @@ -97,8 +94,8 @@ Features * Mix and match imperative and symbolic programming to maximize flexibility and efficiency * Lightweight, memory efficient and portable to smart devices * Scales up to multi GPUs and distributed setting with auto parallelism -* Support for [Python](https://github.com/apache/incubator-mxnet/tree/master/python), [Scala](https://github.com/apache/incubator-mxnet/tree/master/scala-package), [C++](https://github.com/apache/incubator-mxnet/tree/master/cpp-package), [Java](https://github.com/apache/incubator-mxnet/tree/master/scala-package), [Clojure](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package), [R](https://github.com/apache/incubator-mxnet/tree/master/R-package), [Go](https://github.com/jdeng/gomxnet/), [Javascript](https://github.com/dmlc/mxnet.js/), [Perl](https://github.com/apache/incubator-mxnet/tree/master/perl-package), [Matlab](https://github.com/apache/incubator-mxnet/tree/master/matlab), and [Julia](https://github.com/apache/incubator-mxnet/tree/master/julia) -* Cloud-friendly and directly compatible with S3, HDFS, and Azure +* Support for [Python](https://mxnet.incubator.apache.org/api/python), [Scala](https://mxnet.incubator.apache.org/api/scala), [C++](https://mxnet.incubator.apache.org/api/cpp), [Java](https://mxnet.incubator.apache.org/api/java), [Clojure](https://mxnet.incubator.apache.org/api/clojure), [R](https://mxnet.incubator.apache.org/api/r), [Go](https://github.com/jdeng/gomxnet/), [Javascript](https://github.com/dmlc/mxnet.js/), [Perl](https://mxnet.incubator.apache.org/api/perl), [Matlab](https://github.com/apache/incubator-mxnet/tree/master/matlab), and [Julia](https://mxnet.incubator.apache.org/api/julia) +* Cloud-friendly and directly compatible with AWS S3, AWS Deep Learning AMI, AWS SageMaker, HDFS, and Azure License ------- diff --git a/docs/static_site/src/_includes/get_started/get_started.html b/docs/static_site/src/_includes/get_started/get_started.html index 4999518431fd..614b4a409773 100644 --- a/docs/static_site/src/_includes/get_started/get_started.html +++ b/docs/static_site/src/_includes/get_started/get_started.html @@ -256,8 +256,8 @@