ISE 789-002/OR 791-003: Introduction to Support Vector Machines and Neural Networks
Lecture Notes
Lecture 0 | Lecture 1 | Lecture 2 | Lecture 3
Lecture 4 | Lecture 5 | Lecture 6 | Lecture 7
Lecture 8 | Lecture 9
Supplemental Reading Material
- Neural networks and Deep Learning
- Nonlinear Programming and Support Vector Machines
- Support-Vector Networks
- Soft Quadratic Surface SVM
- QSSVM for Semi-Supervised Learning
- Double Well Potential SVM
- Twin-SVM Survey
- Kernel-Free Twin SVM for Multi-classification
- Support Vector Regression Tutorial
- Robust Kernel-Free Support Vector Regression
- Robust SVR for Electric Load Forecasting
- Radial Basis Function Neural Networks Review
- Convolutional Neural Networks Guide
- CNN Cheatsheet
Homework
Assignment #1
Assignment #2 data1 data2
Assignment #3 data1_1 data1_2 data2 data3 data4
Assignment #4 tenstocks
Assignment #5
Assignment #6 letter-recognition
Project
Project Proposal Format
1. Project Proposal Due = November 7, 2022, 6PM
2. Final Project Report Due = Dec 1, 2022, 6PM
Exams
Final Exam: 3:30 P.M. – 6:00 P.M. Tues., Dec. 13, 2022 (NCSU Exam Calendar)
Grades
- Grading of the course is mainly homework-project based (80%).
- Homework/project assignment with each lecture.
- A final exam is expected (20%).