Deep Learning Programming Assignment 1

In the Jupyter notebooks listed below, fill in the code indicated by TODOs in code blocks. You may run the notebook in any environment you wish. Two good options include:

• Google Colab, for which there are links at the top of the notebooks on GitHub, and
• Locally (on your own computer) using PyCharm.

Required

• Notebook 4.3 Deep Neural Networks
• Notebook 5.2 Binary Cross-Entropy Loss
• Notebook 6.3: Stochastic gradient descent
• Notebook 7.1: Backpropagation in Toy Model
• Notebook 8.1: MNIST_1D_Performance
• Notebook 9.1: L2 Regularization

Recommended

All the notebooks from previous chapters, as well as the chapters from which the required notebooks come. You won't submit these extra notebooks, but they will increase your understanding and you may discuss them with me during office hours if you need help or want to dive deeper. We will do some of these notebooks in class.

Submission

Upload the .ipynb files for the notebooks listed under Required above to the assignment on D2L. Please run all code cells before submission so that I can see the results you got. If you are using Google Colab, download the notebook file to your computer with the menu option File -> Download -> .ipynb