Due: November 6th at 11:59pm
In this assignment you will explore classification of handwritten digits with neural networks. For that task, we will use part of the MNIST dataset, which is very commonly used in the machine learning community. Your task is to explore various aspects of multi-layer neural networks using this dataset. We have prepared a small subset of the data with a given split into training and test data.
# Your answer here.
Answer the questions in the cells reserved for that purpose.
Mathematical equations should be written as LaTex equations; the assignment contains multiple examples of both inline formulas (such as the one exemplifying the notation for the norm of a vector $||\mathbf{x}||$ and those that appear on separate lines, e.g.:
$$ ||\mathbf{x}|| = \sqrt{\mathbf{x}^T \mathbf{x}}. $$Submit your report as a Jupyter notebook via Canvas. Running the notebook should generate all the plots and results in your notebook.
Here is what the grade sheet will look like for this assignment. A few general guidelines for this and future assignments in the course:
Grading sheet for the assignment:
Neural networks.
(15 points): Exploration of a network with a single hidden layer
(15 points): Exploration of a network with two hidden layers
(15 points): Regularization
(20 points): Cross-entropy
(20 points): Stochastic gradient descent
(15 points): Linear activation function for regression
Grading will be based on the following criteria: