• How is a grayscale image represented on a computer? How about a color image?
• How are the files and folders in the MNIST_SAMPLE dataset structured? Why?
• Explain how the "pixel similarity" approach to classifying digits works.
• What is a list comprehension? Create one now that selects odd numbers from a list and doubles them.
• What is a "rank-3 tensor"?
• What is the difference between tensor rank and shape? How do you get the rank from the shape?
• What are RMSE and L1 norm?
• How can you apply a calculation on thousands of numbers at once, many thousands of times faster than a Python loop?
• Create a 3×3 tensor or array containing the numbers from 1 to 9. Double it. Select the bottom-right four numbers.
• What is broadcasting?
• Are metrics generally calculated using the training set, or the validation set? Why?
• What is SGD?
• Why does SGD use mini-batches?
• What are the seven steps in SGD for machine learning?
• How do we initialise the weights in a model?
• What is "loss"?
• Why can't we always use a high learning rate?
• What is a "gradient"?
• Do you need to know how to calculate gradients yourself?
• Why can't we use accuracy as a loss function?