IS 425 Resources

Below are some pages I created or some online resources that might help students in my IS 425 sections. I do not test students on this material. It’s really for their enjoyment. This will be sparse initially but I’ll eventually fill it out as I find interesting resources or write stuff myself.

Chapter 2 - Artificial Intelligence

  • Is This AI Trolling Me? - What we consider “artificial intelligence” focuses on the “what” and not the “how.” Sometimes computers are given human characteristics whether the developers intended it or not.

Chapter 4 - Machine Learning

  • Entropy and the 2012 Baltimore Ravens - The course briefly brings up entropy although the students only need to know the definition. Entropy is one of those topics that’s always confused me, so I attempt to make sense of it through the lens of the 2012 Ravens Super Bowl Run.

  • Information Extraction - Weeknd Edition - What makes the music we listen to distinctive? How do humans interpret music and how does that inform any machine learning approaches to analyzing that music?

Chapter 5 - Data Mining Techniques

Chapter 6 - Deep Learning

  • Videos featuring Andrej Karpathy, Director of AI at Tesla:

    • Tesla Autonomy Day - (3 hours) If you skip the first hour of Tesla promo shots, there are several sections to this video. The first section features Andrej talking about AI, the subsequent sections talk about the custom chip designs used in the car.

    • AI for Full-Self Driving - (30 minutes) Since the audience of this video is academic this video is a bit harder to follow. However, it’s a newer video (right before COVID-19) and goes into more technical detail. One of the homework assignments requires watching the video and answering some questions about it.

  • Dirty Tesla - This is a YouTube channel where the host originally tested Tesla’s “enhanced autopilot” functionality on highways and now tests the “full-self driving” functionality on city streets. I like it because he releases 2 videos a week and you can slowly see (over months) the functionality improve. Intersections that were initially problematic are handled better. You even see “2 steps forward, one step back” when regressions cause previously smooth functionality to go bad. Channels like this convince me that while FSD isn’t done, it’s not as far away as people think.

  • Tesla FSD “Through The Eyes” Demo - (3 minutes). A clever and quick insight into what Tesla vehicles see under FSD.

Chapter 9 - Big Data (and GIS)

  • QGIS Map Showcase - One of my assignments has the students make a thematic map based on the results of a k-means clustering. There’s nothing in the assignment that tells the students they have o make a pretty map, so here are some examples of high-quality maps created with the software.

Chapter 10 - Robotics

Chapter 14 - Ethical Implications

  • Humans Need Not Apply - A nice video on the robot revolution and why (this time) the jobs aren’t coming back. It focuses more on the economic implications of the robots.