With the increased adoption of digital solutions, huge amount of data is generated on the web. While this data is readily available on web pages or found in web applications, most of the emphasis in the data analytics world focus more on the predictive modeling aspects and assumes that the data can be easily downloaded from data repositories such as Kaggle. However, this limits the number of AI applications that can be built.
This workshop addresses both the manual mining of web content and predictive modeling of the data. Specifically, students will be taught various systematic techniques on how to mine web content, and how to process the data such as applying predictive modeling and building recommender systems.
Professor Lek Hsiang Hui
Department of Information Systems and Analytics, School of Computing, NUS
Prof Lek received his B.Sc (Hons 1st) and Ph.D from the National University of Singapore in 2008 and 2013 respectively. He started teaching when he was an undergraduate and has taught for more than a decade. During this period, he has won a number of teaching awards such as NUS Annual Teaching Excellence Award (2015/16 and 2016/17), Faculty Teaching Excellence Award (2014/15, 2015/16, 2016/17), and Faculty Teaching Excellence Award Honor Roll (2017/18). Apart from teaching, he has also co-founded a few companies, with the recent one in the area of Big Data Analytics.