Hi all,
Lecture 2: Uncertainty <https://cs50.harvard.edu/summer/ai/2020/lectures/2/> is
now available on the course website. While we've so far focused on
information our AI can know for sure (a game's optimal move, a mine's
location, etc.), we'll now transition to how AI can model uncertain events.
We'll start by looking at the mathematics of probability theory. Then,
we'll explore models — including Bayesian networks and Markov chains — that
AI can use to deal with uncertainty.
For your project this week, you'll have two choices (you only need to
choose one): you can either use a Markov chain approach to implementing
Google's PageRank algorithm for computing the importance of web pages, or
you can use a Bayesian network approach to see how AI can be used to trace
the inheritance of genetic traits through generations.
A few other importance announcements for this week:
- Quiz 2 <https://cs50.harvard.edu/summer/ai/2020/quizzes/2/> is now
available and is due by 11:59pm ET on Wed 7/8. As a reminder, each quiz is
open-book: you may use any and all non-human resources during a quiz, but
the only humans to whom you may turn for help or from whom you may receive
help are the course’s heads.
- Project 2 <https://cs50.harvard.edu/summer/ai/2020/projects/2/> is now
available as well and is due by 11:59pm ET on Sun 7/12. For this project,
you can choose to complete either *Pagerank *or *Heredity*.
- Sections <https://cs50.harvard.edu/summer/ai/2020/sections/> this week
are an opportunity to talk about probability and uncertainty, and ask
questions about this week's concepts. You're highly encouraged to attend!
As always, feel free to reach out to me or any of the course staff with any
questions!
All the best,
Brian
Show replies by date