Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2014"

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{|
 
{|
 
|+ '''Schedule for 10-601 in Fall 2014'''
 
|+ '''Schedule for 10-601 in Fall 2014'''
−
!  Date of lecture
+
!  601A
−
!  Topic
+
!  601B
−
!  Lecturer  
+
!  Topic
 +
!  Lecturer
 
!  Assignment/Notes
 
!  Assignment/Notes
 
|-
 
|-
−
| Tues 9/2||  [[10-601 Introduction to Probability|Overview and Intro to Probability]] || William||  
+
| Wed 8/27|| Tues 9/2||  [[10-601 Introduction to Probability|Overview and Intro to Probability]] ||
 +
| Ziv    || William ||  ||
 
|-
 
|-
−
| Thurs 9/4|| [[10-601 K-NN And Trees|Classification and K-NN]] || William || ''slides will be updated''
+
| Thurs 9/4|| Thurs 9/4|| [[10-601 K-NN And Trees|Classification and K-NN]] || ''slides will be updated''
 +
| Ziv      || William || ||
 
|-
 
|-
−
| Tues 9/9 || | [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || William || ''slides will be updated''
+
| Tues 9/9 || Tues 9/9 || | [[10-601 K-NN And Trees|Decision Trees, and Rule Learning]] || ''slides will be updated''
−
|-
+
| Ziv     || William || ||
−
| Thurs 9/11 || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || William ||
 
−
|-
 
−
| Tues 9/16 ||  [[10-601 Linear Regression|Linear Regression]] || William || ''slides will be updated''
 
−
|-
 
−
| Thurs 9/18 ||  [[10-601 Logistic Regression|Logistic Regression]] || William ||
 
−
|-
 
−
| Tues 9/23 ||  [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William || William's also lecturing in Ziv's class on Mon
 
−
|-
 
−
| Thurs 9/25 ||  Neural networks and Deep Belief Networks || William || ''slides will be updated''
 
−
|-
 
−
|  Tues 9/30* ||  SVMs and Margin Classifiers 1 || Ziv ||  Ziv's also lecturing in his class on Mon
 
−
|-
 
−
| Thurs 10/2* ||  SVMs and Margin Classifiers 2 || Ziv ||  Ziv's also lecturing in his class on Wed
 
−
|-                                                                               
 
−
| Tues 10/7 ||  [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]]  || William ||
 
−
|-                                                                                    
 
−
| Thus 10/9 ||  [[10-601 PAC| PAC Learning]] || William ||
 
−
|-                                                                                    
 
−
| Tues 10/14*  ||  [[10-601 Bias-Variance|Bias-Variance Decomposition]] || William || William's also lecturing in Ziv's class on Mon
 
−
|-                                                                                    
 
−
| Thurs 10/16 || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| William || ''slides to be updated''
 
−
|-                                                                                    
 
−
| Tues 10/21 || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] || Bhavana or Ziv ||    
 
−
|-                                                                                    
 
−
| Thus 10/23  || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]|| Bhavana or Ziv ||
 
−
|-                                                                                    
 
−
| Tues 10/28 || Review session || William || ''slides to be posted''
 
−
|-                                                                                    
 
−
| Thurs 10/30 || '''Mid-term Exam''' || || ''TBA: room and/or time may be different''
 
−
|-                                                                                    
 
−
| Tues 11/4* || [[10-601 GM1| Graphical Models 1]]  || Ziv ||  Ziv's also lecturing in his class on Mon    
 
−
|-                                                                                    
 
−
|  Thurs 11/6* ||  [[10-601 GM2| Graphical Models 2]] || Ziv  || Ziv's also lecturing in his class on Wed
 
−
|-                                                                                    
 
−
|  Tues 11/11* ||  [[10-601 Sequences|HMMS and Sequences]] || Ziv  || Ziv's also lecturing in his class on Mon                                 
 
 
|-
 
|-
−
| Thus 11/13*  || [[10-601 Topic Models|Matrix Factorization and Topic Models]]|| William || William's also lecturing in Ziv's class on Wed, ''slides to be updated''           
+
| Thurs 9/11 || Thurs 9/11 || [[10-601 Naive Bayes|The Naive Bayes algorithm]] ||
 +
| Ziv      || William || ||
 
|-
 
|-
−
| Tues 11/18* ||  [[10-601 Network Models| Network Models]] || William || William's also lecturing in Ziv's class on Mon
+
| Tues 9/16 || Tues 9/16 ||  [[10-601 Linear Regression|Linear Regression]] || ''slides will be updated''
 +
| Ziv      || William || ||
 
|-
 
|-
−
| Thurs 11/20* || Semi-supervised learning || William ||  William's also lecturing in Ziv's class on Wed
+
| Thurs 9/18 || Thurs 9/18 ||  [[10-601 Logistic Regression|Logistic Regression]] ||
−
|-
+
| Ziv      || William || ||
−
|  Tues 11/25* ||  [[10-601 Big Data|Scalable Learning and Parallelization]] || William || William's also lecturing in Ziv's class on Mon
 
 
|-
 
|-
−
| Thurs 11/27 ||''No class - Thanksgiving'' ||  
+
| Tues 9/23 || Tues 9/23 ||  [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William's also lecturing in Ziv's class on Mon
−
|-  
+
| Ziv      || William || ||
−
|  Tues 12/2* ||  Learning and NLP || William ||  
+
|-
 +
| Thurs 9/25 || Thurs 9/25 ||  Neural networks and Deep Belief Networks || ''slides will be updated''
 +
| Ziv      || William || ||
 +
|-
 +
|  Tues 9/30* ||  Tues 9/30* ||  SVMs and Margin Classifiers 1 ||  Ziv's also lecturing in his class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
| Thurs 10/2* || Thurs 10/2* ||  SVMs and Margin Classifiers 2 ||  Ziv's also lecturing in his class on Wed
 +
| Ziv      || William || ||
 +
|-
 +
| Tues 10/7 || Tues 10/7 ||  [[10-601 Evaluation|Evaluating and Comparing Classifiers Experimentally]]  ||
 +
| Ziv      || William || ||
 +
|-
 +
| Thus 10/9 || Thus 10/9 ||  [[10-601 PAC| PAC Learning]] ||
 +
| Ziv      || William || ||
 +
|-
 +
| Tues 10/14*  || Tues 10/14*  ||  [[10-601 Bias-Variance|Bias-Variance Decomposition]] || William's also lecturing in Ziv's class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
| Thurs 10/16 || Thurs 10/16 || [[10-601 Ensembles 1|Ensemble Methods 1]], [[10-601 Ensembles 2|Ensemble Methods 2]]|| ''slides to be updated''
 +
| Ziv      || William || ||
 +
|-
 +
| Tues 10/21 || Tues 10/21 || [[10-601 Clustering| Unsupervised Learning: k-Means and Mixtures]] ||
 +
| Ziv      || William || ||
 +
|-
 +
| Thus 10/23  || Thus 10/23  || [[10-601 DR| Unsupervised Learning: Dimensionality Reduction]]||
 +
| Ziv      || William || ||
 +
|-
 +
-
 +
| Tues 10/28|| Tues 10/28|| Review session || ''slides to be posted''
 +
| Ziv      || William || ||
 +
|-
 +
| Thurs 10/30 || Thurs 10/30 || '''Mid-term Exam''' || ''TBA: room and/or time may be different''
 +
| Ziv      || William || ||
 +
|-
 +
| Tues 11/4* || Tues 11/4* ||  [[10-601 GM1| Graphical Models 1]]  ||  Ziv's also lecturing in his class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
|  Thurs 11/6* ||  Thurs 11/6* ||  [[10-601 GM2| Graphical Models 2]] || Ziv's also lecturing in his class on Wed
 +
| Ziv      || William || ||
 +
|-
 +
|  Tues 11/11* ||  Tues 11/11* ||  [[10-601 Sequences|HMMS and Sequences]] || Ziv's also lecturing in his class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
|  Thus 11/13*  ||  Thus 11/13*  ||  [[10-601 Topic Models|Matrix Factorization and Topic Models]]|| William's also lecturing in Ziv's class on Wed, ''slides to be updated''
 +
| Ziv      || William || ||
 +
|-
 +
|  Tues 11/18* ||  Tues 11/18* ||  [[10-601 Network Models| Network Models]] || William's also lecturing in Ziv's class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
|  Thurs 11/20* ||  Thurs 11/20* ||  Semi-supervised learning ||  William's also lecturing in Ziv's class on Wed
 +
| Ziv      || William || ||
 +
|-
 +
|  Tues 11/25* ||  Tues 11/25* ||  [[10-601 Big Data|Scalable Learning and Parallelization]] || William's also lecturing in Ziv's class on Mon
 +
| Ziv      || William || ||
 +
|-
 +
| Thurs 11/27 || Thurs 11/27 ||''No class - Thanksgiving'' ||
 +
|- Ziv      || William || ||
 +
|
 +
|  Tues 12/2* ||  Tues 12/2* ||  Learning and NLP ||
 +
| Ziv      || William || ||
 +
|-
 +
| Thurs 12/4 || Thurs 12/4 ||  Learning and Biology ||
 +
| Ziv      || William || ||
 
|-
 
|-
−
| Thurs 12/4 ||  Learning and Biology || William  ||
 
−
|-
 
 
|}
 
|}
 +
  
 
'''To other instructors''': if you'd like to use any of the materials found here, you're absolutely welcome to do so, but please acknowledge their ultimate source somewhere.
 
'''To other instructors''': if you'd like to use any of the materials found here, you're absolutely welcome to do so, but please acknowledge their ultimate source somewhere.

Revision as of 17:10, 21 July 2014

This is the syllabus for Machine Learning 10-601 in Fall 2014.

Schedule

-
Schedule for 10-601 in Fall 2014
601A 601B Topic Lecturer Assignment/Notes
Wed 8/27 Tues 9/2 Overview and Intro to Probability Ziv William
Thurs 9/4 Thurs 9/4 Classification and K-NN slides will be updated Ziv William
Tues 9/9 Tues 9/9 Decision Trees, and Rule Learning slides will be updated Ziv William
Thurs 9/11 Thurs 9/11 The Naive Bayes algorithm Ziv William
Tues 9/16 Tues 9/16 Linear Regression slides will be updated Ziv William
Thurs 9/18 Thurs 9/18 Logistic Regression Ziv William
Tues 9/23 Tues 9/23 The Perceptron algorithm William's also lecturing in Ziv's class on Mon Ziv William
Thurs 9/25 Thurs 9/25 Neural networks and Deep Belief Networks slides will be updated Ziv William
Tues 9/30* Tues 9/30* SVMs and Margin Classifiers 1 Ziv's also lecturing in his class on Mon Ziv William
Thurs 10/2* Thurs 10/2* SVMs and Margin Classifiers 2 Ziv's also lecturing in his class on Wed Ziv William
Tues 10/7 Tues 10/7 Evaluating and Comparing Classifiers Experimentally Ziv William
Thus 10/9 Thus 10/9 PAC Learning Ziv William
Tues 10/14* Tues 10/14* Bias-Variance Decomposition William's also lecturing in Ziv's class on Mon Ziv William
Thurs 10/16 Thurs 10/16 Ensemble Methods 1, Ensemble Methods 2 slides to be updated Ziv William
Tues 10/21 Tues 10/21 Unsupervised Learning: k-Means and Mixtures Ziv William
Thus 10/23 Thus 10/23 Unsupervised Learning: Dimensionality Reduction Ziv William
Tues 10/28 Tues 10/28 Review session slides to be posted Ziv William
Thurs 10/30 Thurs 10/30 Mid-term Exam TBA: room and/or time may be different Ziv William
Tues 11/4* Tues 11/4* Graphical Models 1 Ziv's also lecturing in his class on Mon Ziv William
Thurs 11/6* Thurs 11/6* Graphical Models 2 Ziv's also lecturing in his class on Wed Ziv William
Tues 11/11* Tues 11/11* HMMS and Sequences Ziv's also lecturing in his class on Mon Ziv William
Thus 11/13* Thus 11/13* Matrix Factorization and Topic Models William's also lecturing in Ziv's class on Wed, slides to be updated Ziv William
Tues 11/18* Tues 11/18* Network Models William's also lecturing in Ziv's class on Mon Ziv William
Thurs 11/20* Thurs 11/20* Semi-supervised learning William's also lecturing in Ziv's class on Wed Ziv William
Tues 11/25* Tues 11/25* Scalable Learning and Parallelization William's also lecturing in Ziv's class on Mon Ziv William
Thurs 11/27 Thurs 11/27 No class - Thanksgiving
Tues 12/2* Tues 12/2* Learning and NLP Ziv William
Thurs 12/4 Thurs 12/4 Learning and Biology Ziv William


To other instructors: if you'd like to use any of the materials found here, you're absolutely welcome to do so, but please acknowledge their ultimate source somewhere.

Retrieved from "http://curtis.ml.cmu.edu/w/courses/index.php?title=Syllabus_for_Machine_Learning_10-601_in_Fall_2014&oldid=16882"