This shows you the differences between two versions of the page.
Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
schedule [2016/01/12 14:53] anderson |
schedule [2016/05/10 08:46] 127.0.0.1 external edit |
||
---|---|---|---|
Line 1: | Line 1: | ||
====== Schedule ====== | ====== Schedule ====== | ||
- | == January == | + | Follow this link to view all [[https:// |
- | |< 100% 12% 30% 10% 30% 18% >| | + | ===== Announcements ===== |
- | |^ Week ^ Topic ^ Material | + | |
- | | Week 1:\\ Jan 19 - Jan 22 | Overview. | + | |
- | | Week 2:\\ Jan 25 - Jan 29 | | | | + | |
- | == February == | + | **April 29:** My latest neural network code is available at [[http:// |
+ | ===== January ===== | ||
+ | |||
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Feb 1 - Feb 5 | | | + | | Week 1:\\ Jan 19 - Jan 22 | Overview. Intro to machine learning. Python. |
- | | Week 4:\\ Feb 8 - Feb 12 | + | | Week 2:\\ Jan 25 - Jan 29 |
- | | Week 5:\\ Feb 15 - Feb 19 | + | |
- | | Week 6:\\ Feb 22 - Feb 26 | + | |
- | == March == | + | ===== February ===== |
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Feb 29 - Mar 5 | + | | Week 3:\\ Feb 1 - Feb 5 | Ridge regression. Data partitioning. On-line, incremental regression. Regression with fixed nonlinearities. |
- | | Week 8:\\ Mar 7 - Mar 11 | + | | Week 4:\\ Feb 8 - Feb 12 | Nonlinear regression with neural networks. |
- | | Mar 14 - Mar 18 | + | | Week 5:\\ Feb 15 - Feb 19 |
- | | Week 9:\\ Mar 21 - Mar 25 | + | | Week 6:\\ Feb 22 - Feb 26 |
- | | Week 10:\\ Mar 28 - Apr 1 | + | |
- | == April == | + | ===== March ===== |
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Apr 4 - Apr 8 | + | | Week 7:\\ Feb 29 - Mar 5 | Classification, |
- | | Week 12:\\ Apr 11 - Apr 15 | + | | Week 8:\\ Mar 7 - Mar 11 | Classification with neural networks. |
- | | Week 13:\\ Apr 18 - Apr 22 | + | | Mar 14 - Mar 18 |
- | | Week 14:\\ Apr 25 - Apr 29 | + | | Week 9:\\ Mar 21 - Mar 25 |
+ | | Week 10:\\ Mar 28 - Apr 1 | ||
- | == May == | + | ===== April ===== |
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ May 2 - May 6 | | | + | | Week 11:\\ Apr 4 - Apr 8 | Reinforcement Learning |
+ | | Week 12:\\ Apr 11 - Apr 15 | Dimensionality reduction. | ||
+ | | Week 13:\\ Apr 18 - Apr 22 | Nonparametric methods | ||
+ | | Week 14:\\ Apr 25 - Apr 29 | | [[http:// | ||
+ | |||
+ | |||
+ | |||
+ | ===== May ===== | ||
+ | |||
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
+ | ^ Week ^ Topic ^ Material | ||
+ | | Week 15:\\ May 2 - May 6 | Multiple models.\\ PLEASE ATTEND MAY 6th LECTURE TO FILL OUT THE ASCSU STUDENT COURSE SURVEYS! Distance-section students will be filling out the survey on-line. | ||
+ | |||
+ | | Week 16:\\ May 10 | Final Project Notebook Due. | | | Check in final project notebook by Tuesday, May 10th, at 10:00 PM. [[Final Project Report|Here is a summary]] of what is expected in your reportsl | ||