We've prepared a Jupyter notebook that will guide you through the process of creating a deep neural network in TensorFlow.

Make sure you have followed the instructions in the classroom to setup your environment.

Run the following commands from the same directory as the commands above.

$ git clone https://github.com/udacity/RoboND-DNN-Lab.git
$ activate RoboND
$ jupyter notebook

The above will open the jupyter interface in your browser from where you can access the Lab folder and the jupyter notebook DNN_lab.ipynb

The notebook has 4 problems for you to solve:

• Problem 1: Normalize the features
• Problem 2: Use TensorFlow operations to create features, labels, weight, and biases tensors.
• Problem 3: Implement the hidden and output layers for your model.
• Problem 4: Tune the learning rate, number of steps, batch size, and dropout's keep_probability value for the best accuracy.

This is a self-assessed lab.