CS371p Spring 2022: Vincent Huynh
Week of 4 Apr — 10 Apr
- What did you do this past week?
This past week I took an exam and worked on some assignments, including Darwin. I haven’t gotten very far yet, but I plan to really dive into it this weekend. I’ve been consistently going to the gym this week as well.
2. What’s in your way?
I did worse than I expected on my exam this week, but it wasn’t terrible. It didn’t affect my average for the class that much, and I will study harder to bounce back on the final. I also had to drive home this weekend, but I was stuck in some of the worst traffic I’ve seen in a while — people were getting out of their cars and some even drove backward on the feeder road to use the ramp back onto the highway!
3. What will you do next week?
Next week I have more assignments due and another exam. I have been managing my time fairly well this week, so I plan to do the same thing next week. Hopefully, the exam goes better, though. I’m planning to get a lot done on my assignments over the weekend, so I have time to study more next week.
4. What did you think of Paper 11. More getters and setters?
This paper cleared up some questions about the previous paper, especially since the UI getter/setter problem was described but the solution was not really explained until now. I think it’s great that even though some instances of getters and setters are unavoidable, we can still create a design that prevents changes from rippling out to other parts of the code.
5. What was your experience of std::queue, std::priority_queue, std::set, and friends?
I like how we can generalize what we learn about one container to a group of them. For example, vector, deque, and list are sequential containers that container adapters such as stack, queue, and priority queue can use as underlying data structures.
6. What made you happy this week?
Nothing exciting really happened this week, but I’m just happy that I’m able to manage my time well when a lot of exams and assignments are coming up.
7. What’s your pick-of-the-week or tip-of-the-week?
My pick of the week is Magenta: https://magenta.tensorflow.org/. Magenta has trained models for generating music and art using machine learning. I mentioned in my previous post that I had created generative music, and I used Magenta.js to do a lot of the work. You don’t really have to know anything about machine learning to use it since there are some pre-trained models, so it's easy to start working with.
