CMSC 422: Introduction to Machine Learning - Fall 2017

Course Summary and Reading Assignments

Abbreviations:
Marsland = S. Marsland, Machine Learning: An Algorithmic Perspective, 2015
      (some apparent typos in Marsland's text)
Daume = H. Daume, A Course in Machine Learning, 2017 (online access)

 Date Lecture Topics Assigned Readings
Tu 8/29 Learning: Computing's Superpower (pdf)
 
Marsland, pp. 1 - 6
Syllabus
Th 8/31 Supervised Learning (pdf)
 
 
Marsland, pp. 6-11, 19-24
Daume, pp. 8-10, 14-17
Python tutorial: Marsland, 415-423
Tu 9/5 Instance Based Learning (pdf)
 
 
Learning as Search (pdf)
Asg. 1 posted, due Sept. 14
Marsland, 158-167
Daume, 29-34
Aha, IBL Algorithms, 37-43, 48-58 only (pdf)
Mitchell, Concept Learning, 20-25 (pdf)
 
Th 9/7 Learning as Search (pdf)
Inductive Bias (pdf)
Mitchell, Concept Learning, 26-39 (pdf)
 
Tu 9/12 Learning Decision Trees (pdf)
NumPy Basics (pdf)
Marsland, 249-263
Marsland, 11-12, 423-429
Th 9/14 Learning Decision Trees (cont.) (pdf)
NumPy Basics (cont.) (pdf)
Asg. 2 posted, due Sept. 26
see 9/12
see 9/12
Reference: Weka Docs, Download (html)
Tu 9/19 Asg. 1 Review (pdf)
Neural Computation (pdf)
Weka Demo
 
 
Marsland, 15-17, 39-43
see 9/14
Reference: Linear Algebra, 29-40 only (html)
Th 9/21 Perceptrons I (pdf)
Asg. 3 posted
Marsland, 43-64
 
Tu 9/26 Perceptrons II (pdf)
Learning as Gradient Descent (pdf)
 
 
see 9/21
Marsland, 190-192
Daume, 93-94
References: Chain Rule (pdf), Gradient (html)
Th 9/28 Deriving the Delta Rule (pdf)
Error Backpropagation (pdf)
see 9/26
Marsland, 71-83, 100-104
Tu 10/3 Asg. 2 Review (pdf)
Error Backpropagation II (pdf)
Asg. 4 posted
 
Marsland, 84-100, 104-108
 
Th 10/5 Error Backpropagation III:
    Representation & Applications (pdf)
 
see 10/3
Doran, Explainable AI (pdf)
Marsland, 385-388
Tu 10/10 Asg. 3 Review (pdf)
Error Backpropagation IV: Usage (pdf)
 
see 9/28 & 10/3
Th 10/12 Midterm Info (see 10/17)
Deep Learning (pdf)
 
 
Lecun, Deep Learning (pdf)
Lecun, Gradient-Based Learning, 1-12 only (pdf)
Tu 10/17 Midterm Info (pdf)
Asg. 4 Review (pdf)
-- end of midterm topics --
Deep Learning (pdf)
RBF Networks (pdf)
 
 
-- end of midterm readings --
 
Marsland, 111-119
Th 10/19 MIDTERM EXAM     ---
Tu TBA TBA TBA
Th TBA TBA TBA

Midterm Exam: 12:30 pm, Thurs. Oct. 19
Final Exam: 1:30 pm, Mon. Dec. 18

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