• 2024-03-29 Friday

CAAI online science popularization sponsored by the Chinese Association for Artificial Intelligence (CAAI), the Management Committee of Xi'an National Civil Space Industry Base and Shenzhen Dianmao Technology Co., Ltd. will be officially launched at 19:00-20:30 on June 1.


As the core of artificial intelligence, machine learning is an interdisciplinary subject involving probability theory, statistics, approximation theory, convex analysis, algorithmic complexity theory, etc. .With the idea of sharing, communicating and advancing together, the activity will explore the world of machine learning from theory to practice and from the perspective of "how do machines learn".



Lecturer

Zengchang QIN

Associate professor of Beihang University

Chief scientist of Programming Cat APP.

From October 2005 to January 2006, he was a lecturer in the Department of Engineering Mathematics at the University of Bristol, UK, where he studied artificial intelligence and data modeling.

From February 2006 to 2008, he was a distinguished postdoctoral fellow in the Department of Electronics and Computer Science at the University of California, Berkeley, working on text mining and intelligent search.

In March 2008, he joined OPTIMOR Lab at Oxford, United Kingdom, as a research fellow and a visiting fellow in the Department of Statistics at Oxford University.

In 2009, he was inducted into the Ministry of Education's New Century talent support program.

In 2010, he was a visiting scholar at Carnegie Mellon University's Institute for Robotics.

In 2017, his views on artificial intelligence were selected in Agreelist.

Major academic works: Uncertainty Modeling for Data Mining, etc. .


Course Description

Report: How do Machines Learn


Outline:

1. Mechanical thinking

2. From computing to intelligence

3. Learning and generalization

4. The mysteries of high dimensional space

5. Classification and fit

6. Case sharing


Highlights

1. Talking about the nature of machine learning.

2. Providing examples of algorithms to further our understanding of machine learning.


Programming tool: Turtle Editor


How to attend:

1. Live: June 1, 19:00-20:30

2. Welcome to scan the code to enter CAAI online science group

When the group is full, you can add the QR code of the live broadcast assistant. Please note "online science popularization" when you add it.

3. Lecture time: 19:00 -- 20:00

20:00 -- 20:30 after-school communication

Users can communicate with the instructor through the online "question and answer" section




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