Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
Last revision Both sides next revision
en:courses:2016-2017:ml2016 [2016/05/30 14:11]
jaggim
en:courses:2016-2017:ml2016 [2016/09/13 12:08]
ruediger
Line 1: Line 1:
-==== Machine Learning ====+===== Machine Learning ​=====
  
 (a.k.a. Pattern Classification and Machine Learning)\\ (a.k.a. Pattern Classification and Machine Learning)\\
Line 5: Line 5:
  
  
 +\\ 
 +|Instructor|**Martin Jaggi**|
 +|Office|[[http://​plan.epfl.ch/?​room=INJ339|INJ 339]]|
 +|Phone|**+41 21 69 37059**|
 +|Email|**martin.jaggi@epfl.ch**|
 +|Office Hours|**By appointment**|
 +| | |
 +|Instructor|**Ruediger Urbanke**|
 +|Office|[[http://​plan.epfl.ch/?​room=INR116|INR 116]]|
 +|Phone|**+41 21 69 37692**|
 +|Email|**ruediger.urbanke@epfl.ch**|
 +|Office Hours|**By appointment**|
 +\\
 +| | | |
 +|Teaching Assistant |**Mohamad Dia**|Email|**mohamad.dia@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=INR140|INR 140]]|
 +| | |
 +|Teaching Assistant |**Ksenia Konyushkova**|Email|**ksenia.konyushkova@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=BC304|BC304]]|
 +| | |
 +|Teaching Assistant |**Victor Kristof**|Email|**victor.kristof@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=BC204|BC204]]|
 +| | |
 +|Teaching Assistant |**Taylor Newton**|Email|**taylor.newton@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=B1%205%20284.045|B1 Geneva]]|
 +| | |
 +|Teaching Assistant |**Farnood Salehi**|Email|**farnood.salehi@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=BC250|BC250]]|
 +| | |
 +|Teaching Assistant |**BenoĆ®t Seguin**|Email|**benoit.seguin@epfl.ch**| |Office|[[http://​plan.epfl.ch/?​room=INN140|INN 140]]|
 +| | |
 +|Student Assistant |**Frederik Kunstner**|Email|**frederik.kunstner@epfl.ch**|
 +| | |
 +|Student Assistant |**Fayez Lahoud**|Email|**fayez.lahoud@epfl.ch**|
 +| | |
 +|Student Assistant |**Tao Lin**|Email|**tao.lin@epfl.ch**|
 +| | |
 +|Student Assistant |**Arnaud Miribel**|Email|**arnaud.miribel@epfl.ch**|
 +| | |
 +|Student Assistant |**Vidit Vidit**|Email|**vidit.vidit@epfl.ch**|
 +\\
 +
 +|Lectures|**Tuesday** |**8:15 - 10:​00** ​ (Room: [[http://​plan.epfl.ch/?​lang=en&​room=CE%201|CE1]])|
 +|        |**Thursday** |**8:15 - 10:​00** ​ (Room: [[http://​plan.epfl.ch/?​lang=en&​room=CE%204|CE4]])|
 +|Exercises|**Thursday** |**14:15 - 16:​00** ​ (Room: [[http://​plan.epfl.ch/?​lang=en&​room=INF%20119|INF119]],​[[http://​plan.epfl.ch/?​lang=en&​room=INJ218|INJ218]],​[[http://​plan.epfl.ch/?​lang=en&​room=INM11|INM11]],​[[http://​plan.epfl.ch/?​lang=en&​room=INM202|INM202]])|
 +\\
 +|**Language**:​| ​ |English|
 +|**Credits **:|  |7 ECTS|
 +\\ 
 +
 +See the course [[http://​edu.epfl.ch/​coursebook/​en/​pattern-classification-and-machine-learning-CS-433|information]].
 +==== Special Announcements ====
 +  * Practicals: Labs and Projects will be in **Python** this year.
 +  * Projects: There will be two group projects during the course. Project 1 counts 10% and is due Oct 31st. Project 2 counts 30% and is due Dec 22nd.
 +  * For exercises please go to the following rooms: INF119 (A-E); INJ218 (F-M); INM11 (N-Q); INM202 (R-Z)
 +  * Please make sure that you have registered for the course on  [[http://​is-academia.epfl.ch/​|IS-Academia]]. We will provide the PDF lecture notes here and also on [[http://​nb.mit.edu|Nota Bene]] so you can comment & discuss them (see  [[http://​vimeo.com/​7370219|here]]).
 +
 +==== Detailed Schedule ====
 +(tentative, subject to changes)
 +^ Date ^ Topics Covered ^ Exercises ​ ^ Projects ^
 +| 20/9 | Introduction | | |
 +| 22/9 | Linear Regression | Lab 1 | |
 +| 27/9 | Cost Functions | | |
 +| 29/9 | Optimization | Lab 2 | |
 +| 04/10 | Least Squares, ill-conditioning | | |
 +| 06/10 | Maximum Likelihood, Overfitting | Lab 3 | |
 +| 11/10 | Cross-Validation | | |
 +| 13/10 | Bias-Variance decomposition | Lab 4 | |
 +| 18/10 | Classification | | |
 +| 20/10 | Logistic Regression | Lab 5 | |
 +| 25/10 | Generalized Linear Models | | |
 +| 27/10 | k-Nearest Neighbor | Lab 6 | |
 +| 01/11 | Support Vector Machines | | Proj. 1 due 31.10. |
 +| 03/11 | Kernel Regression | Lab 7 | |
 +| 08/11 | Unsupervised Learning | | |
 +| 10/11 | k-Means | Lab 8 | |
 +| 15/11 | Gaussian Mixture Models | | |
 +| 17/11 | EM algorithm | Lab 9 | |
 +| 22/11 | Matrix Factorizations | | |
 +| 24/11 | Recommender Systems | Lab 10 | |
 +| 29/11 | SVD and PCA | | |
 +| 01/12 | SVD and PCA | Lab 11 | |
 +| 06/12 | Neural Networks | | |
 +| 08/12 | Multi-Layer Perceptron | Lab 12 | |
 +| 13/12 | Neural Networks, CNNs | | |
 +| 15/12 | Decision Trees, Random Forests | Lab 13 | |
 +| 20/12 | BayesNet and Belief Propagation | | |
 +| 22/12 | Gaussian Processes | Lab 14 | Project 2 due |
 +
 +==== Textbook ====
 +Christopher Bishop, //Pattern Recognition and Machine Learning// \\
 +Kevin Murphy, //Machine Learning: A Probabilistic Perspective//​ \\
 +Shai Shalev-Shwartz,​ Shai Ben-David, //​Understanding Machine Learning//

Last modified:: %2016/%09/%13 %22:%Sep