Advanced Machine Learning

Dr. HAS Sothea

2025-10-22

• Introduction
• Course Criteria
• Course Sections
• Midterms, Exams and Projects
• Resources and Further Reading

👋 Introduction

Welcome to the Advanced Machine Learning course! This course is designed to provide an in-depth understanding of advanced topics in machine learning, including data comprehension, advanced machine learning methods, optimization approaches, what to watch out when working with each machine learning model, and more. By the end of this course, you will have a solid grasp of various types of datasets, machine learning techniques and be able to apply them to real-world problems.

---

📝 Course Criteria

Criteria	Percentage
Attendance	10%
Participation & quiz	30%
Midterm Exam	30%
Final Project & Presentation	30%

⌨️ Programming: Python with the following main tools and modules:

• Jupyter Notebook
• Google colab
• Scikit-learn
• Pytorch …

---

📋 Course session

Visit the course webpage: M1-DAS: Advanced Machine Learning

Midterms, Exams and Projects

In this section, you will find all the information related to the midterms, exams and projects including instructions, starting dates and the deadlines.

---

📚 Resources and Further Reading

Here, you will find additional resources, including books, research papers, and online courses, to further your understanding of advanced machine learning.

👉� You will find these books helpful…

---