Machine learning & Statistics

1. 2020/12/26 The intuition behind averaging
2. 2020/08/30 FAQ about the Master of Science in Statistics programme in NUS
3. 2020/05/10 A fuller review of my Master of Science in Statistics programme in NUS
4. 2019/05/11 An uncommon approach in tackling class imbalance
5. 2019/03/17 Seven tips for working on analytics delivery projects
6. 2019/02/24 Paper Review: To Tune or Not to Tune the Number of Trees in Random Forest
7. 2019/02/09 My Master of Science in Statistics programme in NUS
8. 2019/01/24 Using waterfall charts to visualize feature contributions
9. 2019/01/21 Worked example on setting up SQL Server with R ODBC connection
10. 2019/01/20 The Machine Learning Life Cycle: how to run a ML project
11. 2019/01/14 Feature Contribution - another way to think about feature importance
12. 2018/12/28 Some data scientist interview questions - with a twist
13. 2018/12/25 Why ensemble modelling works so well - and one often neglected principle
14. 2017/04/12 Quick start to using Git and GitHub
15. 2017/02/14 My learnings on Apache Spark
16. 2017/01/30 Taking a part-time Masters this year in 2017
17. 2016/07/20 Random Forests in R