Comments (4)
@brett1479 I feel like your concept check questions may be close to this type of thing. Do you have some questions that might be good to give in advance of the lecture to build people up to the variable splitting stuff? People were super confused last year.
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Let me know what you think of the first 3 questions here: https://github.com/davidrosenberg/mlcourse-homework/blob/master/in-prep/concept-check-exercises/L1L2Regularization.pdf
Also, should I post it as Lecture 2 Concept Check and then add more to it later, or should it be in a different file PreLecture 2 Concept Check?
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Problem 1 is great. Problem 2 is too hard for a class warmup. We’d either have to give the solutions (and we’d tell people to understand the solutions before class) or we need to give more hints /steps. Problem 3… we should ask for a way to map from a minimizer of the new optimization problem to a minimizer of the original optimization problem.
Let's post it as L1/L2 Lecture Prep -- keep it separate. I'll start a Week 2 block on the webpage.
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https://github.com/davidrosenberg/mlcourse-homework/blob/master/in-prep/concept-check-exercises/L1L2Regularization_sol.pdf
If these solutions look good to you I'll push them
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Related Issues (20)
- New Lab-Length lecture on Generalized Additive Models
- Update lecture 2 concept checks HOT 1
- Make Homework #1 Terminology more consistent with lecture HOT 1
- Make slides and/or notes connecting column correlation with eigenvalues
- Make a note sheet or concept check connecting quadratic form with ellipsoids
- Make SVM figures for non-geometrically motivated soft-margin SVM HOT 1
- Visualize and some basic analysis of explicit feature representation for 1-dim Gaussian kernel HOT 1
- More discussion on stopping conditions of iterative algorithms
- Fix kernel concept check question 1 about min(x,y) HOT 1
- Add title, author name, data(?), etc to Krishna's Contrib materials
- Shouldn't use MAP terminology in Bayes risk context (Concept Check 1) HOT 1
- Undefined notation / notation bug in Lecture 1 Concept Check, Topic 2, Question 1 HOT 3
- Empirical risk level sets when design matrix not full rank HOT 2
- Make numpy broadcasting compulsory in HW#1
- HW#3 Fix read_data function for python3 HOT 1
- More clarity on model that we have figures for in Recitation 1 HOT 1
- Clean up
- Clean up "equivalence" of penalty and constraint form regularization HOT 1
- Illustration / Discussion of exploding & vanishing gradient
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