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anderson [August]
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 ====== Schedule ======
+===== Announcements =====
+Lecture videos will be available.
 /*
-Follow this link to view all [[https://echo.colostate.edu/ess/portal/section/37e
+are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]].
-b6-e68b-4318-89ff-d1ecf025c0b9|lecture videos]].
 */
-===== Announcements =====
-**Feb 28:** In A3, my sample output had incorrect validation errors.  The grading script didn't tell you they were wrong, but your values probably did not exactly match mine.  Enough to cause worry.  Sorry.  They are now corrected in the A3 page.
-**Feb 27:** In the Schedule next to the A2 assignment you will find a link to good examples of reports submitted for A2.
+===== August =====
-Lecture videos are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]].
+|< 100% 10% 20% 30% 20% 20%  >|
+^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
+| Week 1:\\  Aug 21 - Aug 25    | Course overview\\ What is AI?  Promises and fears.\\ Python review.  |   | [[http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0|The Great A.I. Awakening]], by Gideon Lewis-Krause, NYT, Dec 14, 2016.\\ [[https://www.commondreams.org/news/2017/07/19/fundamental-existential-threat-lawmakers-warned-risks-killer-robots|"Fundamental Existential Threat": Lawmakers Warned of the Risks of Killer Robots]]\\ Section 1 of   [[http://www.scipy-lectures.org|Scipy Lecture Notes]]   |  |
+| Week 2:\\ Aug 28 - Sept 1    |     |     |   |
-===== January =====
+===== September =====
 |< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 1:\\  Jan 17 - Jan 20    | Overview. Intro to machine learning. Python.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/01 Course Overview.ipynb|01 Course Overview]],\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/02 Matrices and Plotting.ipynb|02 Matrices and Plotting]],  | [[http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0|The Great A.I. Awakening]], by Gideon Lewis-Krause, NYT, Dec 14, 2016.\\ Section 1 of   [[http://www.scipy-lectures.org|Scipy Lecture Notes]]      |  |
+| Week 3:\\ Sept 4 - Sept 8  |  |  |  |
-| Week 2:\\ Jan 23 - Jan 27    | Probability distributions and regression.    | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/03 Linear Regression.ipynb|03 Linear Regression]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/04 Gaussian Distributions.ipynb|04 Gaussian Distributions]]    |   |
+| Week 4:\\ Sept 11 - Sept 15   |  |  |  |
+| Week 5:\\ Sept 18 - Sept 22   |  |  |  |
+| Week 6:\\ Sept 25 - Sept 29   |  |  |  |
+===== October =====
-===== February =====
+|< 100% 10% 20% 30% 20% 20%  >|
+^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
+| Week 7:\\ Oct 2 - Oct 6  |  |  |  |
+| Week 8:\\ Oct 9 - Oct 13  |  |  |  |
+| Week 9:\\ Oct 16 - Oct 20  |  |  |  |
+| Week 10:\\ Oct 23 - Oct 27  |  |  |  |
+===== November =====
 |< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 3:\\ Jan 30 - Feb 3      | Probabilistic Linear Regression. Ridge regression. Data partitioning. On-line, incremental regression.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/05 Fitting Gaussians.ipynb|05 Fitting Gaussians]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/06 Probabilistic Linear Regression.ipynb|06 Probabilistic Linear Regression]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/07 Linear Ridge Regression and Data Partitioning.ipynb|07 Linear Ridge Regression and Data Partitioning]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/08 Sample-by-Sample Linear Regression.ipynb|08 Sample-by-Sample Linear Regression]]    | | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A1 Linear Regression.ipynb|A1 Linear Regression]] due Monday, January 30th at 10:00 PM.   |
+| Week 11:\\ Oct 30 - Nov 3  |   |  |  |
-| Week 4:\\ Feb 6 - Feb 10   | Regression with fixed nonlinearities. Nonlinear regression with neural networks.\\ Feb 10: Guest Speaker [[https://www.linkedin.com/in/mike-morain-07223710|Mike Morain]], Machine Learning at Amazon, UK.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/09 Linear Regression with Fixed Nonlinear Features.ipynb|09 Linear Regression with Fixed Nonlinear Features]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/10 Nonlinear Regression with Neural Networks.ipynb|10 Nonlinear Regression with Neural Networks]]   | |   |
+| Week 12:\\ Nov 6 - Nov 10  |  |  |  |
-| Week 5:\\ Feb 13 - Feb 17   | Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/10 Nonlinear Regression with Neural Networks.ipynb|10 Nonlinear Regression with Neural Networks]],\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/11 More Nonlinear Regression with Neural Networks.ipynb|11 More Nonlinear Regression with Neural Networks]]   | | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A2 Ridge Regression with K-Fold Cross-Validation.ipynb|A2 Ridge Regression with K-Fold Cross-Validation]] due Monday, February 13th at 10:00 PM.\\ Here are [[A2-good-ones|examples of good A2 reports.]]  |
+| Week 13:\\ Nov 13 - Nov 17  |  |  |  |
-| Week 6:\\ Feb 20 - Feb 24   | Neural Networks. Autoencoders. Guest lectures by our GTA, Jake Lee.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/12 Autoencoder Neural Networks.ipynb|12 Autoencoder Neural Networks]]   | |   |
+|  Nov 20 - Nov 24  |  Fall Break  |
-| Week 7:\\ Feb 27 - Mar 3   | Recurrent Neural Networks.  | \\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/13 Recurrent Neural Networks.ipynb|13 Recurrent Neural Networks]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/14 Introduction to Classification.ipynb|14 Introduction to Classification]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/15 Classification with Linear Logistic Regression.ipynb|15 Classification with Linear Logistic Regression]]   | | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A3 Neural Network Regression.ipynb|A3 Neural Network Regression]] due Wednesday, March 1st at 10:00 PM.  |
+| Week 14:\\ Nov 27 - Dec 1  |  |  |  |
+===== December =====
+|< 100% 10% 20% 30% 20% 20%  >|
+^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
+| Week 15:\\ Dec 4 - Dec 8  |  |  |  |
+| Finals Week:\\ Dec 11 - Dec 15  |   |  |  |

CS440: Introduction to Artificial Intelligence

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