For all readings unless otherwise noted, please write down two non “yes or no” questions and type them into the Google doc I’ve shared with you. Be prepared to discuss the questions/readings in class.

Week 6 (due 12/18)

No assignments this week - please work on your final

Week 5 (due 12/11)

No assignments this week - please work on your final

Week 4 (due 12/4)

The Final (due 12/18)

Choose an image or text data set to explore. This can be an existing API or data set such as a digital museum collection, but it could also be a data set of your own creation such as a website that you scrape or collection of your own photos. Using the tools we covered so far, create an analysis of the visual topology of this collection. When using machine learning to look with a macro lens, what patterns emerge? What narratives are newly exposed with these techniques?

Be sure to collect at least 500-600 data points (images, paragraphs, articles, reviews etc) in order to have enough to analyze. The final deliverable for this class will be a series of images, along with a quick in-class presentation. If you are comfortable with web development, please feel free to create something larger for the midterm.

Presenting the project:

If there are no group projects then we will have less than 10 minutes per person to present, “pecha kucha” style. I will be expecting a fairly concrete and succinct presentation of about 5 minutes.

Metrics for grading:

Before next class, email me:

Week 3 (due 11/20)

Week 2 (due 11/13)

Week 1 (due 2/6)

Follow the instructions below to install Homebrew, Python, and Jupyter notebook

Using the terminal, install Homebrew

First, make sure you have Xcode command-line tools installed. Note - this is not the Xcode editor. These are separate tools that run from your command line. Run the commands below (without the $ at the beginning of the line):

$ xcode-select --install

Next, we install Homebrew by running the following command:

$ ruby -e "$(curl -fsSL"

Run the following command once you’re done to ensure Homebrew is installed and working properly:

$ brew doctor

Next, we install Python

$ brew install python

Check your install with the following command

$ python --version

It should say report a version of python 3 or higher

Next we can use pip, pythons package manager, to install jupyter notebook and other dependencies:

$ pip3 install jupyterlab
$ pip3 install matplotlib

We then run the command below to open a jupyter notebook. Make sure you are in the correct directory when you run this command.

$ jupyter notebook

Please let me know on slack if you are having a hard time with this and I can try and work through it with you before Friday’s class.