2024-02 BME444
BME444: Artificial Neural Systems
Announcement:
- 10th Jan 2024 : Class started
Course syllabus:
- BME444 Course Syllabus
- none
Assessment:
- Midterm exam 25 marks
- Final exam 20 marks
- Miniproject1 30 marks
- Miniproject2 25 marks
Course resources:
- Ebooks: main+code, additional1, additional2, main in part deep learning
- Matlab Essential Commands and Learning preparation
- Chapter00: Course Syllabus
Course resources:
- Ebooks: main+code, additional1, additional2, main in part deep learning
- Matlab Essential Commands and Learning preparation
- Chapter00: Course Syllabus
** Showcase MNIST
- Chapter01: Neuron Model and Network Architecture
Problem1.1, Problem1.2, Problem1.3
- Chapter02: Learning Methods for Single-layer Neural Network
Problem2.0, Problem2.0_sgd, delta.py , delta.m, delta_batch.m, Problem2.1, Problem2.2, Problem2.3, Python for training perceptron
- Chapter03: Learning Methods for Multiple-layer Neural Network
Problem3.1/1, Problem3.1/2 (Batch), Problem3.1/3 , Problem3.1 Test script, Problem3.2 , Problem3.3 , Problem3.4
Tool for forward computing ANN
- Chapter04: Case Studies
o Case1 : Ball Position (Data input, Training data)
o Case2 : Classification by ECG (Data input, Training data)
- Chapter05 : Neuron Network in Practical Development
- Class06: Deep Learning
o Example of model structure: model images
o MNIST (training, testing, database, pretrained model) (more information mnist) (Update code) testTraining data picture: 2, 5, 9
o pima-indians-diabetes (training and testing, database, database description)
o cifar10 (training and testing, pretrained database)
Assignments:
- Instruction
Marks:
- TBA
Last update:9th Jan 2024 20.46