From e4bffc54686f4d8d5bb4355b0d2008c2791b0a24 Mon Sep 17 00:00:00 2001 From: Diego Natali Date: Wed, 24 Oct 2018 16:50:05 +0200 Subject: [PATCH] Update README.md --- building/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/building/README.md b/building/README.md index f35fa34..8558d98 100644 --- a/building/README.md +++ b/building/README.md @@ -33,7 +33,7 @@ First, install development tools and the libraries required to compile MXNet. Ap We are NOT going to use OpenCV, required by MXNet for image processing functions, and NVIDIA CUDA / cuDNN since we do not need to run Apache MXNet with GPU support. -If you want to know more on the dependencies and options to build Apache MXNet from sources, please visit (https://mxnet.incubator.apache.org/install/build\_from\_source.html)[https://mxnet.incubator.apache.org/install/build\_from\_source.html]. +If you want to know more on the dependencies and options to build Apache MXNet from sources, please visit [https://mxnet.incubator.apache.org/install/build\_from\_source.html](https://mxnet.incubator.apache.org/install/build\_from\_source.html). Execute the following commands in your home folder: @@ -131,4 +131,4 @@ aws s3 cp mxnet.tar.gz s3://{your_bucket}/ Now you can run a test by creating an AWS Lambda function starting from the package content and write a simple Python lambda handler that executes some basic MXNet code. Finally, after ensuring the package works as expected, you can terminate the EC2 instance to avoid incurring in unexpected charges. - \ No newline at end of file +