Merge pull request Trusted-AI#39 from ffosilva/master

Examples: Fix typo on credit scoring tutorial

examples/tutorial_credit_scoring.ipynb

@@ -17,7 +17,7 @@
     "\n",
     "The loan scenario describes an intuitive example of illegal bias. However, not all undesirable bias in machine learning is illegal it may also exist in more subtle ways.  For example, a loan company may want a diverse portfolio of customers across all income levels, and thus, will deem it undesirable if they are making more loans to high income levels over low income levels.  Although this is not illegal or unethical, it is undesirable for the company's strategy.\n",
     "\n",
-    "As these two examples illustrate, a bias detection and/or mitigation toolkit needs to be tailored to the particular bias of interest.  More specifically, it needs to know the attribute or attributes, called _protected atrributes_, that are of interest: race is one example of a _protected attribute_ and income level is a second.\n",
+    "As these two examples illustrate, a bias detection and/or mitigation toolkit needs to be tailored to the particular bias of interest.  More specifically, it needs to know the attribute or attributes, called _protected attributes_, that are of interest: race is one example of a _protected attribute_ and income level is a second.\n",
     "\n",
     "### The Machine Learning Workflow\n",
     "To understand how bias can enter a machine learning model, we first review the basics of how a model is created in a supervised machine learning process.  \n",