DSC 140A – Probabilistic Modeling and Machine Learning
This Week
Decision Trees
Redemption Exams on Saturday, Mar 15
Week 9
Regression Revisited
Midterm 02 on Thursday, Mar 06
Homework 9
- Not yet posted...
Was due
Wednesday, Mar 19 at 23:59 PM
Week 8
Naive Bayes
Homework 8
- Not yet posted...
Was due
Wednesday, Mar 05 at 23:59 PM
Week 7
Density Estimation
Homework 7
- Not yet posted...
Was due
Wednesday, Feb 26 at 23:59 PM
Week 6
Kernels & Probabilistic Models
Lecture 11 — Bayes Decision Theory
Homework 6
- Not yet posted...
Was due
Wednesday, Feb 19 at 23:59 PM
Week 5
Regularization
Midterm 01 on Thursday, Feb 06
Homework 5
- Not yet posted...
Was due
Wednesday, Feb 12 at 23:59 PM
Week 4
SVMs
Homework 4
- Not yet posted...
Was due
Wednesday, Feb 05 at 23:59 PM
Week 3
Linear Classification
Lecture 6 — Convexity and Linear Classifiers
Homework 3
- Not yet posted...
Was due
Wednesday, Jan 29 at 23:59 PM
Week 2
Gradient Descent
Homework 2
- Not yet posted...
Was due
Wednesday, Jan 22 at 23:59 PM
Week 1
Introduction
Welcome to DSC 140A!
Here is how to get started:
- Read the syllabus.
- Join our
Campuswire message board
and
Gradescope
with the email invitations you received earlier this week. If
you didn't receive emails, you can use the access code
7229
for Campuswire and the access codeDKVPD2
for Gradescope. - Mark the following important dates/times:
- The first lectures are on
Tuesday, January 07
at
- 11:00 AM in CENTR 212.
- 3:30 PM in CENTR 113.
- The first discussions are:
- Friday, January 10 5:00 PM in CENTR 216.
- Monday, January 13 7:00 PM in CENTR 212.
- This quarter, the exams will be on:
- Midterm 01: Thursday, February 06
- Midterm 02: Thursday, March 06
- Redemption Exams: Saturday, March 15
- Note that the midterms will be held during the regular lecture times (despite what is shown in the official class schedule).
- The first lectures are on
Tuesday, January 07
at
- Try the math self-check below to brush up on the background math.
See you in lecture!
Math Self-Check
DSC 140A builds on a lot of previous math courses. To help you brush up, we've put together an (optional) self-check, consisting of a few short problems that use some of the math facts that you may have forgotten.
We recommend following the instructions at the top of the worksheet. Namely, try the problems first, then check your answers. If you get a problem wrong, find the relevant part of the slides to review the concept.
The math check is optional and will not be turned in.
Lecture 2 — ERM and Least Squares
Homework 1
- Not yet posted...
Was due
Wednesday, Jan 15 at 23:59 PM