Lab: Tensorflow Deep Neural Network

Lab: Tensorflow Deep Neural Network

Previously, you implemented a single neural network on the notMNIST dataset and iterated through tuning different hyperparameters and observing how your network learns accordingly. Now, you will extend that to implement a deep neural network in this lab!

Setup

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

Clone the Repository and Run the Notebook

Run the commands below to clone the Lab Repository and then run the notebook:

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

The jupyter interface will open in your browser. You can then access the cloned repo and the jupyter notebook from there.

Lab Instructions

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. Feel free to discuss with your fellow classmates!