Unit 1: Introduction

Objectives

• Use a Jupyter notebook to run Python code
• Start to uncover how an image classifier works.

Step 0: Log in to your Google account

You can use either your personal account (if you have one) or your Calvin account.

Note: I don’t recommend trying to run this on your own computer at this point; even if you have a compatible GPU, getting Python to work with it can be a project.

Step 1: Jupyter Notebooks

In this section, we’ll practice working with Jupyter notebooks. You may find these references helpful:

• Colab overview
• some parts of the Jupyter Notebooks docs

A number will appear next to each of the code cells when they have run successfully.

Note carefully the difference between Command mode and Edit mode.

I highly encourage you to get comfortable with keyboard shortcuts for the following operations:

• Switch between edit and command mode. (Enter/Return and Esc)
• Insert a cell above or below (a and b)
• Change a cell to code / Markdown (m or y in Command mode)
• Run the current cell (with or without selecting the cell below) (Ctrl-Enter or Shift-Enter)

For more keyboard shortcuts click the Command Palette button on the bottom toolbar on Kaggle (it may be hidden by a cookie consent bar!) or use a search engine.

When you’re done, save your notebook and submit it on Moodle.

Step 2: Image Classifier

In the next section, you’ll work with a basic image classifier.

In this section (and most future Labs), the tasks to do are inside the notebook itself. You’ll find cells labeled Task and blank code chunks usually labeled # your code here. Follow the instructions top-to-bottom, then download and submit when done.

Checklist:

• Did we fill in the table with the accuracy and loss numbers?
• Did we think about whether the predictions are a probability distribution?
• Did we try out using argmax? Can we get it to show the name of the predicted class, not just its number?
• Did we try changing something to see what effect it has on the accuracy?

Objectives

• We feel heard regarding what we’re bringing to this class.
• We support each other as a community.

Instructions

In this week’s Discussion forum, please write a minimally filtered post. This isn’t for showing off; please feel free to not use AI to “polish” these. You may write and post in your native language, but include a translation to English. (If a free translation service doesn’t do a good job, ask me, I’ve got some resources.)

Here’s two things to include:

Part 1: Who are you?

First, tell us how you want people to address you, since sometimes Moodle has a name you don’t actually use, or it’s unclear what pronouns to use.

Tell us some small part of your story. Some ideas:

• Where you grew up and what that was like
• How you ended up at Calvin?
• Some highlights (or difficulties) from your time so far. What have been your favorite classes/instructors (why?), favorite places, …
• What you enjoy doing outside of classes
• What you did over the break (or last summer or whatever)

Keep it short and real.

Part 2: How are you feeling about AI?

Write a short vent about how you’re feeling about AI. What gets you excited? Scared? Overwhelmed? etc.

Then make it actionable: what are you curious about? What do you want to understand better this semester?

You can interpret “AI” either broadly (what’s going on in the world) or narrowly (this half-semester class), it’s up to you.

Optional but recommended: Choose how you will keep yourself updated about AI developments. Browse the sources I suggest or find other ones, pick just one or two (avoid overwhelm), and share which you picked.

Replies

You don’t have to reply, but I encourage you to read what others write and respond to a few of them in a way that makes them feel heard.