diff --git a/7-TimeSeries/3-SVR/README.md b/7-TimeSeries/3-SVR/README.md
index cf5005583faf5131d4bb0b6b66bdc16194ad654f..679bd6b5ca9d6cd7bb276e56219a4c9c5f04e5af 100644
--- a/7-TimeSeries/3-SVR/README.md
+++ b/7-TimeSeries/3-SVR/README.md
@@ -24,7 +24,7 @@ In the last lesson you learned about ARIMA, which is a very successful statistic
 
 The first few steps for data preparation are the same as that of the previous lesson on [ARIMA](https://github.com/microsoft/ML-For-Beginners/tree/main/7-TimeSeries/2-ARIMA). 
 
-Open the _/working_ folder in this lesson and find the _notebook.ipynb_ file.[^2]
+Open the [_/working_](https://github.com/microsoft/ML-For-Beginners/tree/main/7-TimeSeries/3-SVR/working) folder in this lesson and find the _notebook.ipynb_ file.[^2]
 
 1. Run the notebook and import the necessary libraries:  [^2]
 
@@ -383,4 +383,4 @@ This lesson was to introduce the application of SVR for Time Series Forecasting.
 
 
 [^1]: The text, code and output in this section was contributed by [@AnirbanMukherjeeXD](https://github.com/AnirbanMukherjeeXD)
-[^2]: The text, code and output in this section was taken from [ARIMA](https://github.com/microsoft/ML-For-Beginners/tree/main/7-TimeSeries/2-ARIMA)
\ No newline at end of file
+[^2]: The text, code and output in this section was taken from [ARIMA](https://github.com/microsoft/ML-For-Beginners/tree/main/7-TimeSeries/2-ARIMA)