This Week

Neural Networks II

Lecture 14 - Stochastic Gradient Descent

Slides

Lecture 15 - Convolutional Neural Networks

Slides

Notebooks

CNN on CIFAR-10

Homework 7

Was due Wednesday, Feb. 25

Homework 8

Due Wednesday, Mar. 4 at 12:00 AM

Quiz 7

Thursday, Feb. 26

Topic:

Training Neural Networks

Last Week

Neural Networks I

Lecture 12 - Backpropagation

Slides

Lecture 13 - Gradient Descent + PyTorch

Slides

Notebooks

Homework 6

Was due Wednesday, Feb. 18

Quiz 6

Thursday, Feb. 19

Topic:

Neural Networks

Week 6

RBF Networks

Lecture 10 - RBF Networks

Slides

Lecture 11 - Neural Networks

Slides

Homework 5

Was due Wednesday, Feb. 11

Quiz 5

Thursday, Feb. 12

Topic:

Feature Maps and RBF Networks

Week 5

Laplacian Eigenmaps

Midterm 01 was on Thursday, February 5

Lecture 9 - Feature Maps

Slides

Homework 4

Was due Wednesday, Feb. 4

Week 4

Manifold Learning

Lecture 7 - PCA II

Slides

Lecture 8 - Laplacian Eigenmaps

Slides

Homework 3

Was due Wednesday, Jan. 28

Quiz 4

Thursday, Jan. 29

Topic:

PCA

Week 3

PCA

Lecture 5 - Diagonalization and PCA

Slides

Lecture 6 - PCA

Slides

Homework 2

Was due Wednesday, Jan. 21

Quiz 3

Thursday, Jan. 22

Topic:

Eigenvectors and Eigenvalues

Week 2

Eigenvalues and Eigenvectors

Lecture 3 - Matrices

Slides

Lecture 4 - Eigenvectors

Slides

Homework 1

Was due Wednesday, Jan. 14

Quiz 2

Thursday, Jan. 15

Topic:

Linear Transformations

Week 1

Introduction

Welcome to DSC 40B!

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 access code N2YKZY for Gradescope and code 8590 for Campuswire.
The first lectures are on Tuesday, January 06 at 11:00 AM in WLH 2005.

See you in lecture!

Lecture 1 - Introduction

Slides

Lecture 2 - Linear Transformations

Slides

Math Review

The slides linked below review 20 important math facts that we'll use throughout the quarter. You should have seen these concepts in previous courses, so we didn't cover them in lecture, but you might find it helpful to review them.

This review covers just the basics; in the first couple of lectures, we'll review more advanced concepts from linear algebra that you might not remember well (like eigenvalues and eigenvectors).

Quiz 1

Thursday, Jan. 08

Topic:

Basic Math Review

Next Week

CNNs

Midterm 02 on Thursday, March 5

Week 10

Conclusion

Week 11

Finals Week

Redemption Exams on Thursday, March 19