Preprocess notMNIST data and train a neural net on it
We've prepared a Jupyter notebook that will guide you through the process of creating a single layer neural network in TensorFlow.
Run these commands in the terminal to get started:
pip3 install -r requirements.txt
jupyter notebook lab_1.ipynb
This will bring up a browser window with the Jupyter notebook. The notebook has 3 problems for you to solve:
- Problem 1: Normalize the features
- Problem 2: Use operations to create features, labels, weight, and biases tensors
- Problem 3: Tune the learning rate, number of steps, and batch size to classify images from the notMNIST dataset with at least 80% accuracy
This is a self-assessed lab. Compare your answers to the solutions here. If you have any difficulty completing the lab, Udacity provides a few services to answer any questions you might have.
Remember that you can get assistance from your mentor, the forums, or the Slack channel. You can also review the concepts from the previous lessons.