Summer Machine Learning Study Group

NUS Statistics Society carried out a study group on Machine Learning this summer break, where students of diverse backgrounds signed up and came together to complete the course: Introduction to Machine Learning for Coders, by Jeremy Howard. Every week, we had a few students read up and present their findings on both topics that complement those covered by Jeremy, along with other topics of their choice in ML that they wished to share about.

We discussed a variety of topics in ML, including but not limited to: data preprocessing methods and considerations, web scraping, ensembling methods such as random forests and gradient boosting, deep neural net architectures, and reinforcement learning.

We wrapped up the study group by putting the content we learnt into action. Students were encouraged to team up and tackle a Kaggle project of their choice. A diverse array of projects were worked on, including finance, NLP, time series forecasting, and recommendation systems.

Students who contributed to the study group and had completed the project will also be awarded with small vouchers, and a certificate of completion signed by Prof. Chan Hock Peng, Head of the NUS Department of Statistics and Applied Probability, for their efforts.