Machine Learning and Data Analytics

CSCI 480, Spring semester, 2019

 

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Instructor:                 Dr. Shieu-Hong Lin (Description: Description: Description: Description: Description: Description: Description: LinEmail)  

Course Syllabus

Class:                        TR 1:30-2:45 pm at Lim 41

Office Hours:             Lim 137 MW 1:30-3:30pm  T Th 3:00-5:00pm (Reserving a slot by email in advance is encouraged.)

 

Submission of all your work: go to Biola Canvas               Your grades: see them under Biola Canvas

 

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Week 1. Overview of the Landscape of (i) Machine Learning, (ii) the WEKA toolkit, and (iii) the SciPy ecosystem for Data Science

 

Lab # 1: WEKA: Report due: Thursday Jan. 24

 

Reading 1: Report due: Thursday Jan. 24

 

 

Thoughts about Project: Rock-Paper-Scissor as an example

 

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Week 2. Intro to Python and Scipy (I)  |  Machine Learning: Decision Trees

 

Presentation #1 (10-20 minutes each person): Tuesday Jan. 29

 

Lab #2 (Entropy, information gain, and numpy basics):

Exploration: Play with the Jupiter notebook Lab2.ipynb to see how you may calculate the entropy of a given distribution in a numpy array.

 

Reading 2: Report due: Thursday Jan. 31

 

 

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Week 3. Numpy I  |  Machine Learning: Naïve Bayes

 

Presentation #2 (10-20 minutes each person): Tuesday Feb. 5

 

Homework #1: (Decision tree induction based on entropy and information gain): Thursday Feb. 7

 

Reading 3: Report due: Thursday Feb. 7

 

 

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Week 4. Numpy (II) and Pandas (I) 

 

Presentation #3 (10-20 minutes each person): Tuesday Feb. 12

 

Reading 4: Report due: Thursday Feb. 14

 

Lab #3 (Finding information gain given the distribution information stored in a 2-dimensional numpy array): Thursday Feb. 14

 

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Week 5.  More on Numpy (II) and Pandas (I) 

 

Presentation #3 Continued (10-20 minutes each person): Tuesday Feb. 19

 

Reading 5: Report due: Thursday Feb. 21

 

Homework#2 (Naïve Bayes classification): Thursday Feb. 21

 

Lab #4 (Analysis of rock-paper-scissor transcripts using numpy): Thursday Feb. 21

 

 

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Links to online resources

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