This course is designed for the freshman at the School of Business, East China University of Science and Technology. (这是为华东理工大学商学院大一学生开设的课程。)

📚 Overview (课程大纲)

• Lecture 1: Introduction to Machine Learning (机器学习概述)
• Lecture 2: Supervised Learning: Decision Tree (监督学习：决策树)
• Lecture 3: Supervised Learning: Linear Model (监督学习：线性模型)
• Lecture 4: Feature Engineering (特征工程)
• Lecture 5: Model Selection and Explainable Machine Learning (模型选择与可解释性机器学习)
• Lecture 6: Ensemble Learning (集成学习)
• Lecture 7: Unsupervised Learning: Clustering (无监督学习：聚类)
• Lecture 8: Case Study: Recommendation System (案例分析：推荐系统)
• Lecture 9: Case Study: Anomaly Detection (案例分析：异常检测)
• Lecture 10: Basics of Deep Learning (深度学习基础)
• Lecture 11: Convolution Neural Network (图像数据与卷积神经网络)
• Lecture 12: Natural Language Processing (文本数据与自然语言处理)
• Lecture 13: Large Language Model: History and Basic Concepts (大语言模型：发展历史与基础知识)
• Lecture 14: Large Language Model: In-context Learning, RAG and Chain-of-thought (大语言模型：上下文学习、RAG与思维链)
• Lecture 15: AI Agent (AI智能体)
• Lecture 16: Machine Learning Governance and Beyond (机器学习治理与其他)