Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2016"

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This is the syllabus for [[Machine Learning with Large Datasets 10-605 in Fall 2016]].   
 
This is the syllabus for [[Machine Learning with Large Datasets 10-605 in Fall 2016]].   
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 +
----
  
 
Notes:  
 
Notes:  
 
* Homeworks, unless otherwise posted, will be due when the next HW comes out.
 
* Homeworks, unless otherwise posted, will be due when the next HW comes out.
 
* Lecture notes and/or slides will be (re)posted around the time of the lectures.
 
* Lecture notes and/or slides will be (re)posted around the time of the lectures.
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* '''No classes will be held on Oct 4 (Rosh Hashana) or Nov 24 (Thanksgiving)'''
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* Classes are cancelled for Oct 27
 +
* '''No classes will be held on Nov 24 (Thanksgiving)'''
 +
 
 +
----
 +
 
 +
Schedule for 805 projects:
 +
* 11:59pm Sun 10/2: [[Initial 805 project proposal]] due.
 +
* 11:59pm Sun 10/16: Final 805 project proposal due. 
 +
** This is a revised writeup that will address any comments William raises from the initial proposal.
 +
* 11:59pm Sun 11/13: [[Midterm 805 project report]] due.
 +
* '''1:30-2:50pm Tues 12/6: Project presentations''' (in class).  One presentation per group, 12minutes per presentation.  Please send your slide deck to William by '''10am 12/6''' (PDF is best).
 +
* 11:59pm Sun 12/11: [[Machine_Learning_with_Large_Datasets_10-605_in_Fall_2016#Project_Info|Final 805 project writeup]] due.
 +
 
 +
 
 +
----
  
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Schedule:
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Schedule for lectures and 605 assignments:
  
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* Tues Aug 30, 2016 [[Class meeting for 10-605 Overview|Overview]].  Grading policies and etc, History of Big Data, Complexity theory and cost of important operations
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* Tues Aug 30, 2016 [[Class meeting for 10-605 in Fall 2016 Overview|Overview]].  Grading policies and etc, History of Big Data, Complexity theory and cost of important operations
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* Thurs Sep 1, 2016 [[Class meeting for 10-605 Probability Review|Probability Review]].  Counting for big data and density estimation, streaming Naive Bayes, Rocchio and TFIDF
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* Thurs Sep 1, 2016 [[Class meeting for 10-605 in Fall 2016 Probability Review|Probability Review]].  Counting for big data and density estimation, streaming Naive Bayes, Rocchio and TFIDF
 
** '''Start work on''' Assignment 1a: Streaming NB. [http://www.cs.cmu.edu/~wcohen/10-605/assignments/2016-fall/hashtable-nb.pdf Writeup].
 
** '''Start work on''' Assignment 1a: Streaming NB. [http://www.cs.cmu.edu/~wcohen/10-605/assignments/2016-fall/hashtable-nb.pdf Writeup].
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* Tues Sep 6, 2016 [[Class meeting for 10-605 Streaming Naive Bayes|Streaming Naive Bayes]].  Notes on scalable naive bayes, Local counting in stream and sort
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* Tues Sep 6, 2016 [[Class meeting for 10-605 in Fall 2016 Streaming Naive Bayes|Streaming Naive Bayes]].  Notes on scalable naive bayes, Local counting in stream and sort
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* Thurs Sep 8, 2016 [[Class meeting for 10-605 Hadoop Overview|Hadoop Overview]].  Intro to Hadoop, Hadoop Streaming
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* Thurs Sep 8, 2016 [[Class meeting for 10-605 in Fall 2016 Hadoop Overview|Hadoop Overview]].  Intro to Hadoop, Hadoop Streaming
−
** '''Start work on'''  Assignment 1b: Streaming NB on Hadoop. Draft at http://www.cs.cmu.edu/~wcohen/10-605/assignments/2015-spring/stream-nb.pdf, https://drive.google.com/file/d/0BzQQ-spWKjhUd0NXSTB6TW82LWM/view
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** '''Start work on'''  Assignment 1b: Streaming NB on Hadoop. Draft at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw1bhadoopnaivebayes/writeup
 
* Tues Sep 13, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 1]].  Scalable classification, Scalable Rocchio and TFIDF, Abstracts for map-reduce algorithms, Joins in Hadoop, TFIDF in Pig, Guinea Pig intro, TFIDF in Guinea Pig
 
* Tues Sep 13, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 1]].  Scalable classification, Scalable Rocchio and TFIDF, Abstracts for map-reduce algorithms, Joins in Hadoop, TFIDF in Pig, Guinea Pig intro, TFIDF in Guinea Pig
 
* Thurs Sep 15, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 2]].  Similarity joins, Similarity joins with TFIDF, Parallel simjoins
 
* Thurs Sep 15, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 2]].  Similarity joins, Similarity joins with TFIDF, Parallel simjoins
−
** '''Start work on''' Assignment 2: Naive bayes testing in Guinea Pig, draft at https://drive.google.com/file/d/0B-p8_eIVeEHFM1JOSGFWNFFJcU0/view
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** '''Start work on''' Assignment 2: Naive bayes testing in Guinea Pig, draft at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw2nbwithguineapig/writeup
 
* Tues Sep 20, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 3]].  PageRank in Pig, K-means in Pig, Spark, Systems built on top of Hadoop
 
* Tues Sep 20, 2016 [[Class meeting for 10-605 Workflows For Hadoop|Workflows For Hadoop 3]].  PageRank in Pig, K-means in Pig, Spark, Systems built on top of Hadoop
 
* Thurs Sep 22, 2016 [[Class meeting for 10-605 Phrase Finding|Phrase Finding]].  Phrase-finding in Pig, Other work with phrases
 
* Thurs Sep 22, 2016 [[Class meeting for 10-605 Phrase Finding|Phrase Finding]].  Phrase-finding in Pig, Other work with phrases
 
* Tues Sep 27, 2016 [[Class meeting for 10-605 SGD and Hash Kernels|SGD and Hash Kernels]].  Learning as optimization, Logistic regression with SGD, Regularized SGD, Hash kernels for logistic regression
 
* Tues Sep 27, 2016 [[Class meeting for 10-605 SGD and Hash Kernels|SGD and Hash Kernels]].  Learning as optimization, Logistic regression with SGD, Regularized SGD, Hash kernels for logistic regression
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* Thurs Sep 29, 2016 [[Class meeting for 10-605 Parallel Perceptrons|Parallel Perceptrons 1]].  Debugging ML algorithms
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* Thurs Sep 29, 2016 [[Class meeting for 10-605 Parallel Perceptrons|Parallel Perceptrons 1]].  Also wrapup for SGD, debugging ML algorithms
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** '''Start work on''' Assignment 3: scalable SGD Draft at http://curtis.ml.cmu.edu/w/courses/images/8/86/Sgd_fall15.pdf
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** '''Start work on''' Assignment 3: scalable SGD at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw3sgd/writeup
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* Thurs Oct 6, 2016 [[Class meeting for 10-605 Parallel Perceptrons|Parallel Perceptrons 2]].  Structured perceptrons, Interative parameter mixing paper
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* Tues Oct 4, 2016 [[Class meeting for 10-605 Parallel Perceptrons|Parallel Perceptrons 2]].
 +
* Thurs Oct 6, 2016 [[Class meeting for 10-605 Parallel Perceptrons|Parallel Perceptrons 3]].  Structured perceptrons, Interative parameter mixing paper
 
* Tues Oct 11, 2016 [[Class meeting for 10-605 SGD for MF|SGD for MF]].  Matrix factorization, Matrix factorization with SGD, distributed matrix factorization with SGD
 
* Tues Oct 11, 2016 [[Class meeting for 10-605 SGD for MF|SGD for MF]].  Matrix factorization, Matrix factorization with SGD, distributed matrix factorization with SGD
−
* Thurs Oct 13, 2016 [[Class meeting for 10-605 Midterm review|Midterm review]].   
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* Thurs Oct 13, 2016 [[Class meeting for 10-605 Midterm review|Midterm review]].
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** [http://www.cs.cmu.edu/~wcohen/10-605/practice-questions/f2015-midterm.pdf practice questions for midterm from 2015].  This document also references the relevant questions from two previous review sheets:
 +
*** [http://www.cs.cmu.edu/~wcohen/10-605/practice-questions/s2014-final.pdf practice questions from final, 2014]
 +
*** [http://www.cs.cmu.edu/~wcohen/10-605/practice-questions/s2015-final.pdf practice questions for final, 2015]
 +
*** [http://www.cs.cmu.edu/~wcohen/10-605/midterm-review.pdf Some review tips - modified from last year's exam review session]
 
** '''Last assignment due'''
 
** '''Last assignment due'''
 
* Tues Oct 18, 2016 [[Class meeting for 10-605 Midterm|Midterm]].   
 
* Tues Oct 18, 2016 [[Class meeting for 10-605 Midterm|Midterm]].   
 
* Thurs Oct 20, 2016 [[Class meeting for 10-605 Subsampling a Graph|Subsampling a Graph]].  Sampling a graph, Local partitioning
 
* Thurs Oct 20, 2016 [[Class meeting for 10-605 Subsampling a Graph|Subsampling a Graph]].  Sampling a graph, Local partitioning
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** '''Start work on''' Assignment 4: Subsampling a Graph with Approximate PageRank, draft at https://drive.google.com/file/d/0BzQQ-spWKjhUaWoyOFZHV21uUlU/view
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** '''Start work on''' Assignment 4: Subsampling a Graph with Approximate PageRank, draft at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw4approximatepagerank/writeup
 
* Tues Oct 25, 2016 [[Class meeting for 10-605 Deep Learning|Deep Learning 1]].  Deep learning intro, Deep learning and GPUs, Expressiveness of MLPs, Exploding and vanishing gradients, Modern deep learning models
 
* Tues Oct 25, 2016 [[Class meeting for 10-605 Deep Learning|Deep Learning 1]].  Deep learning intro, Deep learning and GPUs, Expressiveness of MLPs, Exploding and vanishing gradients, Modern deep learning models
−
* Thurs Oct 27, 2016 [[Class meeting for 10-605 Deep Learning|Deep Learning 2]].  Reverse-mode differentiation, Recursive ANNs, Word2vec
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* Thurs Oct 27, 2016. '''No class.'''
−
* Tues Nov 1, 2016 [[Class meeting for 10-605 Randomized Algorithms|Randomized Algorithms 1]].  Bloom filters, The countmin sketch
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* Tues Nov 1, 2016 [[Class meeting for 10-605 Deep Learning|Deep Learning 2]].  Reverse-mode differentiation, Recursive ANNs, Word2vec
−
** '''Start work on''' Assignment 5: Autodiff with IPM.  This is a new assignment for Fall 2016.
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* Thurs Nov 3, 2016 [[Class meeting for 10-605 Randomized Algorithms|Randomized Algorithms 1]].  Bloom filters, The countmin sketch
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* Thurs Nov 3, 2016 [[Class meeting for 10-605 Randomized Algorithms|Randomized Algorithms 2]].  Locality sensitive hashing
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** '''Start work on''' Assignment 5: Autodiff with IPM.  This is a new assignment for Fall 2016. View writeup at https://github.com/KarandeepJohar/10605-f16-hw5/blob/master/automatic-reverse-mode.pdf
−
* Tues Nov 8, 2016 [[Class meeting for 10-605 Graph Architectures for ML|Graph Architectures for ML]].  Graph-based ML architectures, Pregel, Signal-collect, GraphLab, PowerGraph, GraphChi, GraphX
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* Tues Nov 8, 2016 [[Class meeting for 10-605 Randomized Algorithms|Randomized Algorithms 2]].  Locality sensitive hashing
−
* Thurs Nov 10, 2016 [[Class meeting for 10-605 SSL on Graphs|SSL on Graphs]].  Semi-supervised learning intro, Multirank-walk SSL method, Harmonic fields, Modified Adsorption SSL method, MAD with countmin sketches
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* Thurs Nov 10, 2016 [[Class meeting for 10-605 Graph Architectures for ML|Graph Architectures for ML]].  Graph-based ML architectures, Pregel, Signal-collect, GraphLab, PowerGraph, GraphChi, GraphX
−
* Tues Nov 15, 2016 [[Class meeting for 10-605 Unsupervised Learning On Graphs|Unsupervised Learning On Graphs]].  Spectral clustering, Power iteration clustering, Label propagation for clustering non-graph data, Label propagation for SSL on non-graph data
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* Tues Nov 15, 2016 [[Class meeting for 10-605 SSL on Graphs|SSL on Graphs]].  Semi-supervised learning intro, Multirank-walk SSL method, Harmonic fields, Modified Adsorption SSL method, MAD with countmin sketches
−
** '''Start work on''' Assignment 6: To be decided, possibly using Spark/GraphX to do PIC or MRW.
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* Thurs Nov 17, 2016 [[Class meeting for 10-605 Unsupervised Learning On Graphs|Unsupervised Learning On Graphs]].  Spectral clustering, Power iteration clustering, Label propagation for clustering non-graph data, Label propagation for SSL on non-graph data
−
* Thurs Nov 17, 2016 [[Class meeting for 10-605 Parameter Servers|Parameter Servers]]. 
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** '''Start work on''' Assignment 6: Phrase-finding with Spark. Writeup at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw6phrasefindingwithspark/writeup
 
* Tues Nov 22, 2016 [[Class meeting for 10-605 LDA|LDA 1]].  DGMs for naive Bayes, Gibbs sampling for LDA
 
* Tues Nov 22, 2016 [[Class meeting for 10-605 LDA|LDA 1]].  DGMs for naive Bayes, Gibbs sampling for LDA
−
** '''Start work on''' Assignment 7: LDA with a Parameter Server, draft http://curtis.ml.cmu.edu/w/courses/images/1/16/Hw7-lda-ps.pdf
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* Tues Nov 29, 2016 [[Class meeting for 10-605 Parameter Servers|Parameter Servers]].
−
* Tues Nov 29, 2016 [[Class meeting for 10-605 LDA|LDA 2]].  Parallelizing LDA, Fast sampling for LDA, DGMs for graphs
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** '''Start work on''' Assignment 7: LDA with a Parameter Server, Writeup at https://autolab.andrew.cmu.edu/courses/10605-f16/assessments/hw7lda/attachments/677
−
* Thurs Dec 1, 2016 [[Class meeting for 10-605 Scalable Probabilistic Logics|Scalable Probabilistic Logics]]. 
+
* Thurs Dec 1, 2016 [[Class meeting for 10-605 LDA|LDA 2]].  Parallelizing LDA, Fast sampling for LDA, DGMs for graphs
−
* Tues Dec 6, 2016 [[Class meeting for 10-605 Review session for final|Review session for final]].
+
* Tues Dec 6, 2016 [[Class meeting for 10-605 Project Reports|Project Reports]].
 
** '''Last assignment due'''
 
** '''Last assignment due'''
−
* Thurs Dec 8, 2016 [[Class meeting for 10-605 Final Exam|Final Exam]].
+
* Thurs Dec 8, 2016 [[Class meeting for 10-605 Final Exam|Final Exam]].  Note that we've posted:
 +
** [http://www.cs.cmu.edu/~wcohen/10-605/practice-questions/s2014-final.pdf practice questions from final, 2014]
 +
** [http://www.cs.cmu.edu/~wcohen/10-605/practice-questions/s2015-final.pdf practice questions for final, 2015]
 +
** Comments:
 +
*** Most of the exam (approximately 80%) covers material from after the midterm.
 +
*** You may bring in '''two''' 8 1/2 by 11 sheets of paper with notes.

Latest revision as of 11:54, 11 August 2017

This is the syllabus for Machine Learning with Large Datasets 10-605 in Fall 2016.

Notes:

  • Homeworks, unless otherwise posted, will be due when the next HW comes out.
  • Lecture notes and/or slides will be (re)posted around the time of the lectures.
  • Classes are cancelled for Oct 27
  • No classes will be held on Nov 24 (Thanksgiving)

Schedule for 805 projects:

  • 11:59pm Sun 10/2: Initial 805 project proposal due.
  • 11:59pm Sun 10/16: Final 805 project proposal due.
    • This is a revised writeup that will address any comments William raises from the initial proposal.
  • 11:59pm Sun 11/13: Midterm 805 project report due.
  • 1:30-2:50pm Tues 12/6: Project presentations (in class). One presentation per group, 12minutes per presentation. Please send your slide deck to William by 10am 12/6 (PDF is best).
  • 11:59pm Sun 12/11: Final 805 project writeup due.


Schedule for lectures and 605 assignments:

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