diff --git a/README.md b/README.md
index 71460f97..a6b21dc7 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@ Amazon SageMaker Operators for Kubernetes are operators that can be used to trai
 
 ## Usage
 
-First, you must [install the operators](). After installation is complete, create a TrainingJob YAML specification by following one of the samples, like [samples/xgboost-mnist-trainingjob.yaml](./samples/xgboost-mnist-trainingjob.yaml). Then, use `kubectl` to create and monitor the progress of your job:
+First, you must [install the operators](https://sagemaker.readthedocs.io/en/stable/amazon_sagemaker_operators_for_kubernetes.html). After installation is complete, create a TrainingJob YAML specification by following one of the samples, like [samples/xgboost-mnist-trainingjob.yaml](./samples/xgboost-mnist-trainingjob.yaml). Then, use `kubectl` to create and monitor the progress of your job:
 
 ```bash
 $ kubectl apply -f xgboost-mnist-trainingjob.yaml
@@ -37,7 +37,7 @@ xgboost-mnist-cf1e16fb10a511eaaa450a350733ba06/algo-1-1574811611 2019-11-26 15:4
 
 The Amazon SageMaker Operators for Kubernetes enable management of SageMaker TrainingJobs, HyperParameterTuningJobs, BatchTransformJobs and HostingDeployments (Endpoints). Create and monitor them using the same `kubectl` tool as above.
 
-To install the operators onto your Kubernetes cluster, follow our [User Guide]().
+To install the operators onto your Kubernetes cluster, follow our [User Guide](https://sagemaker.readthedocs.io/en/stable/amazon_sagemaker_operators_for_kubernetes.html).
 
 ### YAML Examples