update url links (oneapi-src#882)

Author: jingxu10

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_Extensions_AutoMixedPrecision/README.md

@@ -1,27 +1,27 @@
 # `Intel® Extension for PyTorch* Getting Started` Sample
 
-Intel Extension for PyTorch* is a Python package to extend the official PyTorch. It is designed to make the Out-of-Box user experience of PyTorch CPU better while achieving good performance. The extension also will be the PR(Pull-Request) buffer for the Intel PyTorch framework dev team. The PR buffer will contain functions and optimization (for example, take advantage of Intel's new hardware features).
+Intel Extension for PyTorch\* is a Python package to extend the official PyTorch. It is designed to make the Out-of-Box user experience of PyTorch CPU better while achieving good performance. The extension also will be the PR(Pull-Request) buffer for the Intel PyTorch framework dev team. The PR buffer will contain functions and optimization (for example, take advantage of Intel's new hardware features).
 
-For comprehensive instructions goto the github repo for [Intel Extension for PyTorch*](https://github.com/intel/intel-extension-for-pytorch).
+For comprehensive instructions goto the github repo for [Intel Extension for PyTorch\*](https://github.com/intel/intel-extension-for-pytorch).
 
 | Optimized for                       | Description
 |:---                               |:---
-| OS                                | Linux* Ubuntu* 18.04
+| OS                                | Linux\* Ubuntu\* 18.04
 | Hardware                          | Skylake with GEN9 or newer
-| Software                          | Intel Extension for PyTorch*;
-| What you will learn               | How to get started with Intel Extension for PyTorch*
+| Software                          | Intel Extension for PyTorch\*;
+| What you will learn               | How to get started with Intel Extension for PyTorch\*
 | Time to complete                  | 60 minutes
 
 
 ## Purpose
 
-You will learn how to download, compile, and get started with Intel Extension for PyTorch* from this sample code.
+You will learn how to download, compile, and get started with Intel Extension for PyTorch\* from this sample code.
 
 The code will be running on the CPU.
 
 ## Key Implementation Details 
 
-The code includes Intel Extension for PyTorch* and Auto-mixed-precision.
+The code includes Intel Extension for PyTorch\* and Auto-mixed-precision.
 
 ## License  
 
@@ -32,10 +32,10 @@ Third party program Licenses can be found here: [third-party-programs.txt](https
 
 ## Building the `Intel Extension for PyTorch* Getting Started` Sample
 
-### On a Linux* System 
+### On a Linux\* System 
 
-Please follow instructions [here](https://github.com/intel/intel-extension-for-pytorch#installation).
+Please follow instructions [here](https://intel.github.io/intel-extension-for-pytorch/tutorials/installation.html).
 
 ## Running the Sample
 
-Please follow instructions [here](https://github.com/intel/intel-extension-for-pytorch#getting-started).
+Please follow instructions [here](https://intel.github.io/intel-extension-for-pytorch/tutorials/examples.html#id3).

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_TorchCCL_Multinode_Training/README.md

@@ -11,9 +11,9 @@ For comprehensive instructions regarding distributed training with oneCCL in PyT
 
 | Optimized for                       | Description
 |:---                               |:---
-| OS                                | Linux* Ubuntu* 18.04
+| OS                                | Linux\* Ubuntu\* 18.04
 | Hardware                          | Skylake with GEN9 or newer
-| Software                          | Intel Extension for PyTorch*;
+| Software                          | Intel Extension for PyTorch\*;
 | What you will learn               | How to perform distributed training with oneCCL in PyTorch
 | Time to complete                  | 60 minutes
 
@@ -37,7 +37,7 @@ Third party program Licenses can be found here: [third-party-programs.txt](https
 
 ## Building the `torch-ccl Getting Started` Sample
 
-### On a Linux* System 
+### On a Linux\* System 
 
 Please follow instructions [here](https://github.com/intel/optimized-models/tree/master/pytorch/distributed#distributed-training-with-oneccl-in-pytorch).