(2024) Artificial Intelligence & Machine Learning (Nantes Master)


Instructor:       Qili Gao(高琦丽)
Email:              qlgao@szu.edu.cn
Room:             Huixing Building-Classroom 4
Time:               周五 7-10节
Credits:           2/32 课时


Table of Contents

Grade breakdown

Requirements Percent Points Note
Attendance 15% 100
In-class Assignment 10% 100
Small Project 15% 100
Final Project 60% 100

Class Schedule

Week Topic
1 Introduction to Artificial Intelligence & Machine Learning & Linear Regression
2 Logistic Regression
3 Multi-Classification
4 Model Evaluation (In-class Assignment)
5 Decision Tree (ID3 & C4.5 & CART)
6 BP Neural Network & Optimization
7 Small Project (HR Analytics for Employee Rentension)
8 Convolutional Neural Network (CNN)
9 Ensemble Learning (RF & Adaboost & GBDT)
10 Recurrent Neural Network (RNN/LSTM/GRU)
11 Unsupervised Learning (Clustering & PCA)