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Schedule

Announcements

February 13: Assignment A2 has been updated and now contains link to A2grader.tar.

Lecture videos are available at this CS445 video recordings site.

January

Week Topic Material Reading Assignments
Week 1:
Jan 16 - Jan 19
Overview. Intro to machine learning. Python. 01 Course Overview
02 Matrices and Plotting
From Python to Numpy, Chapters 1 - 2
Deep Learning, Chapters 1 - 5.1.4
Week 2:
Jan 22 - Jan 26
Fitting linear models to data as a direct matrix calculation, and incrementally using stochastic gradient descent (SGD) 03 Linear Regression
04 Linear Regression Using Stochastic Gradient Descent (SGD)
Week 3:
Jan 29 - Feb 2
Ridge regression. Data partitioning. Probabilistic Linear Regression. Regression with fixed nonlinearities. 05 Linear Ridge Regression and Data Partitioning
06 Probabilistic Linear Regression
07 Linear Regression with Fixed Nonlinear Features
Deep Learning, Section 7.3
The Great A.I. Awakening, by Gideon Lewis-Krause, NYT, Dec 14, 2016.
A1 Linear Regression due Wednesday, January 31, 10:00 PM. Here are some good solutions.

February

Week Topic Material Reading Assignments
Week 4:
Feb 5 - Feb 9
Introduction to nonlinear regression with neural networks. 08 Stochastic Gradient Descent with Parameterized Activation Function
09 Scaled Conjugate Gradient for Training Neural Networks
Deep Learning, Chapter 6 (skip 6.2)
Week 5:
Feb 12 - Feb 16
Lectures on Feb 12th and 14th are canceled. Friday, more neural networks 10 More Nonlinear Regression with Neural Networks
Week 6:
Feb 19 - Feb 23
Autoencoders. Activation functions. 11 Autoencoder Neural Networks Searching for Activation Functions, by Ramachandran, Zoph, and Le]] A2 Neural Network Regression due Tuesday, February 20, 10:00 PM
Week 7:
Feb 26 - Mar 2
Classification. LDA and QDA. K-Nearest Neighbors. A3 Activation Functions due Thursday, March 1, 10:00 PM

March

Week Topic Material Reading Assignments
Week 8:
Mar 5 - Mar 9
Classification with Neural Networks
Mar 12 - Mar 16 Spring Break
Week 9:
Mar 19 - Mar 23
Analysis of Trained Networks. Bottleneck Networks. Classifying Hand-Drawn Digits.
Week 10:
Mar 26 - Mar 30
Convolutional Neural Networks

April

Week Topic Material Reading Assignments
Week 11:
Apr 2 - Apr 6
Reinforcement Learning. Games using Tabular Q functions.
Week 12:
Apr 9 - Apr 13
Reinforcement Learning using Neural Networks as Q functions.
Week 13:
Apr 16 - Apr 20
Unsupervised Learning. Dimensionality Reduction. Clustering.
Week 14:
Apr 23 - Apr 27
Support Vector Machines.

May

Week Topic Material Reading Assignments
Week 15:
Apr 30 - May 4
Ensembles. Other topics.
May 7 - May 10 Final Exams
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