MA 415   Machine Learning
CSSE 415 Machine Learning

Instructors: Team taught by Yosi Shibberu and Rachel Petrik

Course Prerequisites:
Junior standing and MA212, and either MA223 or MA381, and one of CHE310, CSSE220, ECE230, MA332, MA386 or (ME323 or ME327).

Course Description

More powerful and cheaper computing and large data sets have made machine learning possible for a wide range of products and applications. In this course, we study the mathematics underlying the most successful machine learning algorithms used in practice today.

Course Topics

• linear and logistic regression
• support vector machines
• decision trees, bagging, boosting and random forests
• k-means clustering
• under/over-fitting and the variance/bias trade-off
• model regularization and validation
• the curse of dimensionality
• dimensionality reduction methods
• student project on an advanced topic

Course Textbooks

1. The Hundred-Page Machine Learning Book by Andriy Burkov. (optional)
2. An Introduction to Statistical Learning by G. James, D. Witten, T. Hastie and R. Tibshirani. This book is free.

Software

We will use the Python based package Scikit-Learn.

Past Student Projects

1. UFC Match Outcome Predictor
   Evan Cruse, Alex Ketchan, Jack Kovacs, Andrew Walkowski
2. Predicting the Outcome of an MLB At-Bat Using Machine Learning
   Cooper Brotherton, Max Chaplin, Danielle Villa, Michael Yager
3. Pokemon Showdown Win Prediction
   John Bass, Ray Fang, James Kelley, Jacob Ritenour
4. Predicting Flight Delays
   Brendan Boewe, Nathaniel Craan, Jake Nickel, Wojciech Zacherek
5. Stroke Prediction
   Yutong Chen, Bowen Ding, Mashangjun Li, Jiadi Wang
6. Kings County Housing
   Steven Feng, Aditya (Laya) Mehra
7. Fraud Detection
   Jason Cramer, David Gottlieb, Leding Ren, Nick von Bulow
8. League Of Legends Winning Team
   Ainsley Liu, Sybil Chen, Wendy Ju, Yunpu Zhang
9. Weather Prediction
   Joey Hatfield, Trey Kline, Zach Kelly, Jonathan Moyers
10. F1 Race Prediction
    Campbell Garvin, Andrew Kosikowski, Dalton Julian, Braxton Lee
11. Steam Games, A Machine Learning Project
    Li Da, Will Yelton, Cullen LaKemper, Travis Zheng
12. U.S. Equities Analysis
    Jared Brown, Shengjun Guan, Thomas Nandola, Amruth Pabba
13. Heart Attack Prediction
    Meghna Allamudi, Kyle Brown, Ezenna CMadu, Vanskika Reddy
14. Flight Delay Prediction
    Jiafan Lin, Achintya Gupta, Chengquian Lyu, Evan Cochran, Zijian Huang
15. Video Game Sales Prediction
    Landon Bundy, Anand Desai, Joey Hegg, Jack McGlynn
16. Examining the Factors Related to the Opioid Epidemic Proliferation
    James Brandewie, Luke Ferderer, Jayden Foshee, Elliya Sorenson
17. Expedia Hotel Recommendation
    Cehong Wang, Haozhe Wu, Qiyue Gao, Shantao Cao
18. Crytocurrency
    Ben Goldstein, Ian Lim, Haulein McInerney, Dylan Scheumann
19. Job Change Analysis
    Xusheng Liu, Jerry Zheng, Wenzing Li
20. TAP Scores
    Aman Bajaj, Derek Grayless, Eric Kirby, Arjun Mahajan
21. MBTI Personality Prediction from Internet Posts
    Ian Landwehr, Jessica Myers, William Thesken, Andrea Wynn
22. Predicting Strokes
    Jared Petrisko, Luke McNeil, Connor Schulte, Cody Steiner
23. Improving Predictability Using the General Social Survey
    Eric Tu, Aditya Burle, Jeremiah Wooten, Simon Snider
24. Job Change Analysis
    Xusheng Liu, Jerry Zheng, Wenxing Li
25. Code Autocomplete
    Jake Bellis, Justin Calareso, Zach Glover
26. Stock Market Price Predictions
    Samuel Flickinger, Jacob Hendrich, Nick Nie, Jacob Petrisko
27. StackOverflow Tag Prediction
    Nihaal George, Brevin Lacy, Tommy McMichen, Wes Siebenthaler
28. Recognizing Friendliness of City Squirrels
    Terry Cheney, Jackson Hajer, Christian Meinzen, Bohdan Vakhitov
29. Predicting Cardiovascular Disease
    Darius Daugvila, Aaron Glave, Matthew Lyons, Miranda Masters
30. YouTube Data Analysis
    Bowen Feng, Howard Hu, Jing Lin, Yuchen Zhao
31. Predicting Movie Success
    Ash Fowler, Trey Fuentes, Megan Hawksworth, Addi Reynolds
32. Digit Recognition
    Xiangnan Chen, Augustine Cui, Qinghong Wu, Valentine Wu
33. Used Car Value Predictor
    Natalie Allen, Jason Chen, Dominic Grazioli
34. Nine Men’s Morris
    Sterling Hayden, Quinn McKown, Hao Yang
35. Inter-State Traffic Volume
    Carlos Feng, Xingheng Lin, Allen Liu, Wenze Ma
36. Breast Cancer Prediction
    Lingyun Li, Max Wang, Yiyuan Wang, Tiantian Zhang
37. Heart Disease Rate Prediction
    Xiangbei Chen, Ming Lyu, Picheng Tang, Yuankai Wang, Kaiyu Xie
38. Predicting House Prices in Ames, Iowa
    Adam Baker, Cobi Illian, Aaron Kulinowski, Johann Ryan, Andrew Sturdevant
39. Using Gradient Boosted Trees to Predict the Success or Failure of Kickstarter Projects
    Katana Colledge, Kathi Munoz, Parker Phillips, Phillip Tyler, Oscar Youngquist
40. Forecasting Chicago Temperature
    Akanksha Chattopadhyay, Wenkang Dang, Bryan Gish, Cade Jin, Scott Sun
41. Predicting World Series Performance with Machine Learning
    Ty Adams, Rohit Chandra, John Lambrecht, Tyrus Sooneborn
    
42. Using Machine Learning to Assess Possibility of Radio Communication
    Tom Joyner, Manoj Kurapati, Erik Stockwell
43. Predicting Use of Force by Seattle Law Enforcement
    Mariana Lane, Ishan Saraf, Anirudh Singh, Austin Stieglitz, Jennifer Wohlpart
44. Using Global Media Data to Predit Asset Prices
    Collin Moore, Leela Pakanati, John Michael Van Treeck, Jack Wassom, Justin Willoughby
45. Identifying Fruit Attributes by Image
    Eric Moorman, Christopher Nurrenburg, Alex Schmalzl, Han Wei
46. Neural Networks Attempt to Mimic Several Functions
    Austin Derrow-Pinion, Kice Sanders, Aaron Bartee
47. Predicting the Popularity of Online News
    Yuzong Gao
48. Creating a Virtual Physicist
    Jared Hoffman
49. Sentiment Analysis of Tweets about Presidential Candidates
    Steven Rasp
50. RI/O: An Artificial Intelligence Based on the Neural Evolution of Augmented Topologies Algorithm, Adam Finer, David Lam, Xiao Xin, Runzhi Yang
51. Music Genre Classification,
    Ryan Dick, Addison Williams
52. Drone Detection,
    Christian Owen, Asher Morgan, Tommy Mulc, Andy Yuk
53. Using Machine Learning to Balance Call of Duty Gameplay,
    Phillip Shepard, Qikai Huang
54. Predicting World Series Performance with Machine Learning,
    Ty Adams, Rohit Chandra, John Lambrecht, Tyrus Sonneborn
55. Using Machine Learning to Assess Possibility of Radio Communication,
    Tom Joyner, Manoj Kurapati, Erik Stockwell
56. Predicting Use of Force by Seattle Law Enforcement,
    Mariana Lane, Ishan Saraf, Anirudh Singh, Austin Stieglitz, Jennifer Wohlpart
57. Using Global Media Data to Predict Asset Prices,
    Collin Moore, Leela Pakanati, John Michael Van Treeck, Jack Wassom, Justin Willoughby
58. Identifying Fruit Attributes by Images,
    Eric Moorman, Christopher Nurrenburg, Alex Schmalzl, Han Wei
59. Dota2 Line-up Helper
60. Target Tracking by Vision
61. Predicting Breast Cancer with Cell Images