Neural Networks

An introductory course on neural networks by Dr. Michael S. Gashler.

This course guides students to implement their own neural network code. It also covers a variety of neural net concepts, including basic theory, mathematical derivation, intuition, and some speculation about future directions, but the primary emphasis is on implementation. Students are assumed to already be proficient at computer programming in C++ or Java. The programming assignments are a critical component of this course, and watching the lectures without completing the assignments does not even count as taking the course.

Lecture 1 Matrix multiply	Lecture 2 Regression	Lecture 3 Error surfaces	Lecture 4 Cross-validation
Lecture 5 Model space	Lecture 6 OLS	Lecture 7 Starter code	Lecture 8
Lecture 9	Lecture 10	Lecture 11	Lecture 12
Programming Assignment 1 Linear Regression
Lecture 13	Lecture 14	Lecture 15	Lecture 16
Assigned Readings 1
Lecture 17	Lecture 18	Lecture 19	Lecture 20
Lecture 21	Lecture 22	Lecture 23	Lecture 24
Assigned Readings 2
Lecture 25	Lecture 26	Lecture 27	Lecture 28
Lecture 29	Lecture 30	Lecture 31	Lecture 32
Programming Assignment 2 Backpropagation
Lecture 33	Lecture 34	Lecture 35	Lecture 36
Lecture 37	Lecture 38	Lecture 39	Lecture 40
Rest Presentation 1
Lecture 41	Lecture 42	Lecture 43	Lecture 44
Lecture 45	Lecture 46	Lecture 47	Lecture 48
Programming Assignment 3 Using Neural Nets
Exam 1
Lecture 49	Lecture 50	Lecture 51	Lecture 52
Lecture 53	Lecture 54	Lecture 55	Lecture 56
Lecture 57	Lecture 58
Programming Assignment 4 Convolutional Layers
Lecture 59	Lecture 60	Lecture 61	Lecture 62
Exam 2
Lecture 63	Lecture 64	Lecture 65	Lecture 66
Programming Assignment 5 Time Series Regression
Lecture 67	Lecture 68	Lecture 69	Lecture 70
Lecture 71	Lecture 72	Lecture 73	Lecture 74
Rest Presentation 2
Lecture 75	Lecture 76	Lecture 77	Lecture 78
Lecture 79	Lecture 80	Lecture 81	Lecture 82
Programming Assignment 6 State Inference for Modeling a Dynamical System
Lecture 83	Lecture 84	Lecture 85	Lecture 86
Lecture 87	Lecture 88	Lecture 89	Lecture 90
Assigned Readings 3
Lecture 91	Lecture 92	Lecture 93	Lecture 94
Lecture 95	Lecture 96	Lecture 97	Lecture 98
Lecture 99
Final Exam
Certificate