Subject
Mathematics
Program
PhD
Location
Côte-des-Neiges
Instruction mode
Credits
3
Description
Deep learning has achieved great success in a variety of fields such as speech recognition, image understanding, and natural language understanding. This course aims to introduce the basic techniques of deep learning and recent progress of deep learning on natural language understanding and graph analysis.
This course aims to introduce the basic techniques of deep learning including feedforward neural networks, convolutional neural networks, and recurrent neural networks. We will also cover recent progress on deep generative models. Finally, we will introduce how to apply these techniques to natural language understanding and graph analysis.
Themes covered
Machine Learning Basics
Feedforward Neural Networks Optimization Tricks
Convolutional Neural Networks
Recurrent Neural Networks
Deep Learning for Natural Language Understanding
Deep Learning for Analyzing graphs/networks
Deep Generative Models
Important notes
Course in French : MATH 80648
Equivalent course(s) : MATH 60630(A) or MATH 80600(A)
Préalable(s) : MATH 60600(A) ou MATH 60629(A) ou MATH 80629(A) ou être admis au Doctorat (Ph. D.).
Préalable(s) : MATH 60600(A) ou MATH 60629(A) ou MATH 80629(A) ou être admis au Doctorat (Ph. D.).