Updated readme

Author: chhayac

README.md

@@ -16,5 +16,5 @@
 | Autoencoders using Fashion MNIST| [Autoencoder_Fashion_MNIST.ipynb](https://github.com/chhayac/Machine-Learning-Notebooks/blob/master/Autoencoder_Fashion_MNIST.ipynb)| Building an autoencoder as a classifier using Fashion MNIST dataset. |
 | Logistic Regression| [Logistic_Regression.ipynb](https://github.com/chhayac/Machine-Learning-Notebooks/blob/master/Logistic_Regression.ipynb)| Built a logistic regression model from scratch |
 | Fuzzy string matching| [fuzzy_string_matching.ipynb](https://github.com/chhayac/Machine-Learning-Notebooks/blob/master/fuzzy_string_matching.ipynb)| To study how to compare strings and determine how similar they are in Python. |
-| Spam email classification| [spam_email_classification.ipynb]()| Built a spam detection classification model using an email dataset.
-| Customer churn prediction| [customer_churn_prediction.ipynb]()| To predict if customers churn i.e. unsubscribed or cancelled the service.
+| Spam email classification| [spam_email_classification.ipynb](https://github.com/chhayac/Machine-Learning-Notebooks/blob/master/spam_email_classification.ipynb)| Built a spam detection classification model using an email dataset.
+| Customer churn prediction| [customer_churn_prediction.ipynb](https://github.com/chhayac/Machine-Learning-Notebooks/blob/master/customer_churn_prediction.ipynb)| To predict if customers churn i.e. unsubscribed or cancelled the service.