In this part we implement a full project with a Regression problem. We learn how to download, analyze, and preprocess data with pandas. We then build a simple Linear Model using the keras.Dense layer and predict new values. Then extend this model to a deep neural network and learn about the importance of activation functions.

All code and slides from this course can be found on GitHub.

Links:

• https://www.tensorflow.org

Code is based on:

• https://www.tensorflow.org/tutorials/keras/regression