FACULTY OF AGRICULTURALSCIENCES AND TECHNOLOGIES / BIOSYSTEMS ENGINEERING / BSM4040 - DEEP LEARNING

Contents Of The Courses in a weekly Period

Week 
Subjects 
Sources 
1The Math Behind Machine Learning: Linear Algebra[1] p. 1-15
2The Math Behind Machine Learning: Statistics[1] p. 15-25
3A Review of Machine Learning[1] p. 26-40
4Neural Networks[1] p. 41-80
5Fundamentals of Deep Networks[1] p. 80-95
6Common Architectural Principles of Deep Networks[1] p. 96-105
7Unsupervised Pretrained Networks[1] p. 105-123
8Convolutional Neural Networks (CNNs)[1] p. 125-142
9Recurrent Neural Networks[1] p. 143-159
10Recursive Neural Networks[1] p. 160-164
11Building Deep Networks[1] p. 165-174
12Modeling CSV Data with Multilayer Perceptron Networks[1] p. 175-182
13Modeling Handwritten Images Using CNNs[1] p. 183-210
14Tuning Deep Networks[1] p. 237-250