CSC 4220: Data Mining and Machine Learning

Tennesse Tech, Spring 2025

Welcome to Week 14 of CSC4220!

Schedule

Week 0

Jan 22

Lecture 0 Introduction: Note 0

Week 1

Jan 27

Lecture 1 Python and Pandas I: Note 1

Jan 29

Lecture 2 Pandas II and Pandas III: Note 2A Note 2B

Homework 1 (due Feb 7) Homework 1

Drop Deadline (w/o grade) 11:59pm CT

Week 2

Feb 3

Lecture 3 Pandas Fin and In-Class Exercise: Income Dataset; In-Class Notebook

Feb 5

Lecture 4 In-Class Exercise Part 2 and Probability: In-Class Notebook

Feb 7

Homework 1 Due

Grad Book Reading Make selection and notify instructor

Week 3

Feb 10

Lecture 5 Distributions, Sampling, and Statistics: Salary Questionare; In-Class Notebook

Feb 12

Lecture 6 Expectation, Variance, Correlation, and Hypothesis Testing: In-Class Debrief

Homework 2 (due Feb 21) Homework 2

Week 4

Feb 17

Lecture 7 Exploratory Data Analysis: In-Class Notebook

Feb 19

Lecture 8 Snow Day!

Feb 21

Grad Project Project proposal due

Homework 2 Due

Week 5

Feb 24

Lecture 9 Modeling: In-Class Notebook; Section 2.1, 2.2, and 3.1 in ISLP

Feb 26

Lecture 10 The Problem of Multiple Regression: In-Class Notebook; Section 3.2 in ISLP

Homework 3 (due March 16) Homework 3

Week 6

March 3

Lecture 11 Gradient Descent Part 1: In-Class Notebook; Section 10.7 in ISLP

March 5

Lecture 12 Gradient Descent Part 2: In-Class Notebook; Section 10.7 in ISLP

Midterm Exam

Week 7

March 10

Lecture 13 Model Evaluation: Section 2.2, 3.1, and 3.2 in ISLP; On a Linear Model; On a Neural Network

March 12

Midterm

March 16

Homework 3 Due

Week 8

March 17: Spring Break! No Class
March 19: Spring Break! No Class

Week 9

March 24

Lecture 14 Model Regularization: In-Class Notebook; Section 6.0, 6.1, 6.2 in ISLP

March 26

Lecture 15Logistic Regression: In-Class Notebook; Section 4.3 in ISLP

March 28

Grad Project Background literature review due

Grad Book Reading Due Book Club

Week 10

March 31

Lecture 16 Logistic Regression part 2: Page 405 in ISLP; In-Class Notebook

April 2

Lecture 17 Model Evaluation: Solution for Monday; In_Class Notebook

April 4

Project Project Details

Week 11

April 7

Lecture 18 Neural Networks: Chapter 10 in ISLP; Solution to ICE; In-Class Exercise

April 9

Lecture 19 Neural Networks Part 2: Chapter 10 in ISLP; In-Class Exercise 1; In-Class Exercise 2

Homework 4 Read chapter 10 and complete exercises 1 through 9 - submit an .ipynb file containing the completed exercises.

Week 12

April 14

Lecture 20 RNNs, CNNs, and Transformers: In-Class Example

April 16

Lecture 21 Decision Trees: In-Class Spreadsheet

April 18

Grad Project Implementation Demonstration and Follow up Questions Due

April 20

Homework 4 Due

Week 13

April 21

Lecture 22 Clustering: KMeans Sheet; In-Class Exercise; DBScan

Homework 5 Read sections 8.1 and 12.4 and complete exercise 9 (part a through h) in chapter 8 and exercise 3 in chapter 12.

April 23

Lecture 23 Ethics: What is Ethics?; ML Ethics Videos

Week 14

April 27

Homework 5 Due

April 28

Lecture 24 Natural Language Processing and How LLMs work: GPT-2; BERT Topic

April 30

Lecture 25 Review Day

May 2

Grad Project Final Results

Week 15

May 6: Final Exam Final Exam 1-3pm CT : Final Exam Schedule