Khoa Toán-Tin học Đại học Khoa học Tự nhiên TPHCM tổ chức các khóa học ngắn:
Mini-Lecture: An Introduction to Machine Learning

Lecturer:

Hien Tran

Alumni Distinguished Graduate Professor

Department of Mathematics

North Carolina State University

What is Machine Learning?

“Machine learning teaches computers to do what come naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. The algorithms adaptively improve their performance as the number of samples available for leaning increases” (from MathWorks, Natick, MA)

Why Machine Learning Matters?

Artificial intelligence will impact our civilization more than any innovation this century. Anyone who does not understand it will soon find themselves in a world full of technology that feels more and more like witchcraft. From Apple SIRI to self-driving cars to design evidence-based treatment plans for cancer patients, artificial intelligence is progressing at an astonishing rate.

In this mini-lecture series, we will explore the core machine learning concepts behind those technologies. Machine learning is a subfield of artificial intelligence. A machine learning’s algorithm enables it to identify patterns in observed data and predicting things without relying on explicit pre-programmed rules and models.

Topics to be covered (if time allows):

• Supervised Learning

  • Support vector machines (SVMs)

  • K-nearest neighbors

• Unsupervised Learning

  • K-means clustering

  • Principal component analysis (PCA), singular value decomposition

• Feature Selection

• Model Evaluation

  • ROC curve, confusion matrix, accuracy, hypothesis testing

Schedule:

Tuesday, March 6
Lecture:    9:00-10:00
Break:    10:00-10:15
Lecture:    10:15-11:15

Wednesday, March 7
Lecture:     9:00-10:00
Break:    10:00-10:15
Lecture:    10:15-11:15

optional: Wednesday, March 7 afternoon

Khóa học không thu phí, không tính tín chỉ, mọi người quan tâm nghiêm túc có thể dự. Người muốn dự cần đăng kí theo mẫu ở đây. Người đăng kí sẽ được nhận thông tin tiếp theo về khóa học.