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====== Schedule ====== | ====== Schedule ====== | ||
- | == January == | + | Follow this link to view all [[https:// |
- | |< 100% 20% 20% 20% 30% 10% >| | + | ===== Announcements ===== |
+ | |||
+ | **May 9:** At the bottom of this page is a link to a summary of the content expected in your project reports. | ||
+ | |||
+ | **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 1:\\ Jan 19 - Jan 22 | Overview. Intro to machine learning. Python. | + | | Week 1:\\ Jan 19 - Jan 22 | Overview. Intro to machine learning. Python. |
- | | Week 2:\\ Jan 25 - Jan 29 | Probability distributions and regression. | + | | Week 2:\\ Jan 25 - Jan 29 | Probability distributions and regression. |
- | == February == | + | ===== February |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 20% 20% 30% 10% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 3:\\ Feb 1 - Feb 5 | Nonlinear regression with neural networks. | + | | Week 3:\\ Feb 1 - Feb 5 | Ridge regression. Data partitioning. On-line, incremental regression. Regression with fixed nonlinearities. |
- | | Week 4:\\ Feb 8 - Feb 12 | Recurrent neural networks. | + | | Week 4:\\ Feb 8 - Feb 12 | Nonlinear regression with neural networks. |
- | | Week 5:\\ Feb 15 - Feb 19 | + | | Week 5:\\ Feb 15 - Feb 19 |
- | | Week 6:\\ Feb 22 - Feb 26 | Classification, | + | | Week 6:\\ Feb 22 - Feb 26 | Classification, |
- | == March == | + | ===== March ===== |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 20% 20% 30% 10% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 7:\\ Feb 29 - Mar 5 | Classification with neural networks. | + | | Week 7:\\ Feb 29 - Mar 5 |
- | | Week 8:\\ Mar 7 - Mar 11 | Convolutional, | + | | Week 8:\\ Mar 7 - Mar 11 |
| Mar 14 - Mar 18 | Spring Break! | | Mar 14 - Mar 18 | Spring Break! | ||
- | | Week 9:\\ Mar 21 - Mar 25 | Nonparametric methods. | | 8.1-8.10 | + | | Week 9:\\ Mar 21 - Mar 25 | Bottleneck, and deep networks. | [[http:// |
- | | Week 10:\\ Mar 28 - Apr 1 | Dimensionality reduction. | | 6.1-6.8, 6.10-6.13 | | + | | Week 10:\\ Mar 28 - Apr 1 | Convolutional neural nets. Clustering. | [[http:// |
- | == April == | + | ===== April ===== |
- | |< 100% 20% 20% 20% 30% 10% >| | + | |< 100% 20% 20% 30% 10% 20% >| |
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 11:\\ Apr 4 - Apr 8 | Clustering | + | | Week 11:\\ Apr 4 - Apr 8 | Reinforcement Learning |
- | | Week 12:\\ Apr 11 - Apr 15 | Support vector machines. | + | | Week 12:\\ Apr 11 - Apr 15 | Dimensionality reduction. | |
- | | Week 13:\\ Apr 18 - Apr 22 | Reinforcement learning. | + | | Week 13:\\ Apr 18 - Apr 22 | Nonparametric methods |
- | | Week 14:\\ Apr 25 - Apr 29 | Multiple models. | | 17.1-17.12 | | + | | Week 14:\\ Apr 25 - Apr 29 | | [[http:// |
- | == May == | ||
- | |< 100% 20% 20% 20% 30% 10% >| | + | |
+ | ===== May ===== | ||
+ | |||
+ | |< 100% 20% 20% 30% 10% 20% >| | ||
^ Week ^ Topic ^ Material | ^ Week ^ Topic ^ Material | ||
- | | Week 15:\\ May 2 - May 6 | | | + | | 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 | ||
+ | |||
+ | Selected Project Reports (in no particular order): | ||
+ | |||
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