03_1_preclass4wed.md

Week 3: Preclass homework for Wednesday

There is no class on Monday due to the public holiday. If you can't get all of this done by class on Wednesday, at least watch the videos in task 4 and 5 because I'll be moving forward from there.

1. Review updated slides from week 2

I updated slides from week 2 Mon and Wed to reflect what we actually covered and to include your work on algorithm exercises, linear regression, and data science workflow.

2. Class Q & A forum

I decided to use Piazza for Q&A (rather than slack). This is where you can ask (and answer) questions about homework, coding issues, or anything else. I haven't used Piazza before but here's what looks great: anonymous questions, collaborative answers (wiki style editing), student privacy, FERPA compliant, web interface or phone app.

• Watch for an invitation to sign up.
• Log in and ask a question!
• https://piazza.com/colorado/fall2022/ebio5460002

3. Video lecture: further topics on repetition structures

Some new material to complete repetition structures

• 03_2_slides_repetition_structures_further.pdf
• 03_2_video_repetition_structures_further.md

4. Programming problems on repetition structures

• 03_3_repetition_structures_problem_set.md
• Push to GitHub

5. Video lecture: 3 classes of algorithms

We're now starting algorithms in data science. This is an overview.

• 03_4_slides_3classes_algorithms4ds.pdf
• 03_4_video_3classes_algorithms4ds.md (11 mins)

6. Video lecture: Introduction to training algorithms

Training algorithms are central to all of data science. In class you'll translate the pseudocode for the grid search algorithm to R code and use it on your data. So, you might start pondering how to do that.

• 03_5_slides_training_algorithm.pdf
• 03_5_video_training_algorithm.md - 17 mins