Lessons learnt working on applied machine learning research

During my internship at Taipei Medical University, I was working on developing predictive models for Chronic Kidney Disease. The project was an educational experience with challenges that arose from the complexity and large size of the dataset. In this article, I will share the key lessons I learnt that helped me boost my productivity as a beginning researcher. The ideas are quite general and applicable to most machine learning workflows. Some of them are obvious ones that we choose to ignore.