Merge pull request #110 from labFareb/patch-1

Fix typo in broken link

1-Introduction/1-intro-to-ML/README.md

@@ -21,7 +21,7 @@ Before starting with this curriculum, you need to have your computer set up and
 - **Learn Python**. It's also recommended to have a basic understanding of [Python](https://docs.microsoft.com/learn/paths/python-language/?WT.mc_id=academic-15963-cxa), a programming language useful for data scientists that we use in this course.
 - **Learn Node.js and JavaScript**. We also use JavaScript a few times in this course when building web apps, so you will need to have [node](https://nodejs.org) and [npm](https://www.npmjs.com/) installed, as well as [Visual Studio Code](https://code.visualstudio.com/) available for both Python and JavaScript development.
 - **Create a GitHub account**. Since you found us here on [GitHub](https://github.com), you might already have an account, but if not, create one and then fork this curriculum to use on your own. (Feel free to give us a star, too 😊)
-- **Explore Scikit-learn**. Familiarize yourself with [Scikit-learn]([https://scikit-learn.org/stable/user_guide.html), a set of ML libraries that we reference in these lessons.
+- **Explore Scikit-learn**. Familiarize yourself with [Scikit-learn](https://scikit-learn.org/stable/user_guide.html), a set of ML libraries that we reference in these lessons.
 
 ### What is machine learning?