R

I just returned from PSI conference 2018. I got a chance to give an oral present at session “Step into the Real World”. I shared my experience from taking part in Roche Advanced Analytics Data (RAAD) Challenge. The take-home message is “with available wealthy real-world data and the power of machine learning for such data, statisticians would be benefit to know machine learning methods”. You can read my slides “Predict survival for cancer patients using real world data: simple model or advanced machine learning?

To build a website via Blowdown, an easy way is to let Netlify to build an initial website for you once you have GitHub account. For example, if you use “Academic” theme, go to Install Academic with Netlify. Nelify will create a repository academic-kickstart (you can change the name) under your GitHub account and provide you with a customizable URL to access your new site. On GitHub, go to your newly created repository and edit config.

Sometimes it takes quite a lot time to grasp one new method (such as machine learning); on the other hand, you may just need less than half an hour to learn one skill. R Markdown is the latter one but change your way of working. My experience of using R Markdown since 2006 for statistical analysis and reporting mainly focused on exploratory analysis. The reports generated were word/pdf/html documents. I have not worked on a real example of slides format yet (except simple demo with one or two slides).