added lesson_10.html

README.md

@@ -99,7 +99,7 @@ By ensuring that the content aligns with projects, the process is made more enga
 |      07       |                North American pumpkin prices 🎃                |        [Regression](2-Regression/README.md)         | Build linear and polynomial regression models                                                                                   |        <ul><li>[Python](2-Regression/3-Linear/README.md)</li><li>[R](2-Regression/3-Linear/solution/R/lesson_3.html)</li></ul>        |      <ul><li>Jen and Dmitry</li><li>Eric Wanjau</li></ul>       |
 |      08       |                North American pumpkin prices 🎃                |        [Regression](2-Regression/README.md)         | Build a logistic regression model                                                                                               |     <ul><li>[Python](2-Regression/4-Logistic/README.md) </li><li>[R](2-Regression/4-Logistic/solution/R/lesson_4.html)</li></ul>      |      <ul><li>Jen</li><li>Eric Wanjau</li></ul>       |
 |      09       |                          A Web App 🔌                          |           [Web App](3-Web-App/README.md)            | Build a web app to use your trained model                                                                                       |                                                 [Python](3-Web-App/1-Web-App/README.md)                                                  |                         Jen                          |
-|      10       |                 Introduction to classification                 |    [Classification](4-Classification/README.md)     | Clean, prep, and visualize your data; introduction to classification                                                            | <ul><li> [Python](4-Classification/1-Introduction/README.md) </li><li>[R](4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb)  | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
+|      10       |                 Introduction to classification                 |    [Classification](4-Classification/README.md)     | Clean, prep, and visualize your data; introduction to classification                                                            | <ul><li> [Python](4-Classification/1-Introduction/README.md) </li><li>[R](4-Classification/1-Introduction/solution/R/lesson_10.html)  | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
 |      11       |             Delicious Asian and Indian cuisines 🍜             |    [Classification](4-Classification/README.md)     | Introduction to classifiers                                                                                                     | <ul><li> [Python](4-Classification/2-Classifiers-1/README.md)</li><li>[R](4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
 |      12       |             Delicious Asian and Indian cuisines 🍜             |    [Classification](4-Classification/README.md)     | More classifiers                                                                                                                | <ul><li> [Python](4-Classification/3-Classifiers-2/README.md)</li><li>[R](4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
 |      13       |             Delicious Asian and Indian cuisines 🍜             |    [Classification](4-Classification/README.md)     | Build a recommender web app using your model                                                                                    |                                              [Python](4-Classification/4-Applied/README.md)                                              |                         Jen                          |