Semester:  Spring 2021, also offered on Fall 2019 and Fall 2018 
Time and place:  Monday, Wednesday and Friday, 10.30am11.20am EST 
Instructor:  Jean Honorio, Lawson Building 2142J (Please send an email for appointments) 
TAs: 
Kevin Bello, email: kbellome at purdue.edu, Office hours: Monday 1pm3pm EST Prerit Gupta, email: gupta596 at purdue.edu, Office hours: Friday 2pm4pm EST Chuyang Ke, email: cke at purdue.edu, Office hours: Tuesday 2pm4pm EST Jin Son, email: son74 at purdue.edu, Office hours: Thursday 3pm5pm EST Anxhelo Xhebraj, email: axhebraj at purdue.edu, Office hours: Wednesday noon2pm EST Kaiyuan Zhang, email: zhan4057 at purdue.edu, Office hours: Tuesday 10amnoon EST 
Date  Topic (Tentative)  Notes 
Wed, Jan 20  Lecture 1: introduction  Python 
Fri, Jan 22  Lecture 2: probability review (joint, marginal and conditional probabilities)  
Mon, Jan 25 
(lecture continues) Lecture 3: statistics review (independence, maximum likelihood estimation) 

Wed, Jan 27  (lecture continues)  
Fri, Jan 29  Lecture 4: linear algebra review 
Linear algebra in Python Homework 1: due on Feb 5, 11.59pm EST 
Mon, Feb 1  Lecture 5: elements of data mining and machine learning algorithms  
Wed, Feb 3 
(lecture continues) Lecture 6: linear classification, perceptron 

Fri, Feb 5  — 
Homework 1 due Homework 1 solution 
Mon, Feb 8  (lecture continues)  
Wed, Feb 10 
(lecture continues) Lecture 7: perceptron (convergence), support vector machines (introduction) 

Fri, Feb 12  (lecture continues)  Homework 2: due on Feb 19, 11.59pm EST 
Mon, Feb 15  (lecture continues)  
Wed, Feb 17  READING DAY  
Fri, Feb 19  Lecture 8: generative probabilistic modeling, maximum likelihood estimation, classification  Homework 2 due 
Mon, Feb 22 
(lecture continues) Lecture 9: generative probabilistic classification (naive Bayes), nonparametric methods (nearest neighbors) 
Homework 3: due on Mar 1, 11.59pm EST 
Web, Feb 24 
(lecture continues) Lecture 10: nonparametric methods (classification trees) 

Fri, Feb 26 
(lecture continues) Case Study 1 