Non-linear growth curves with Stan

I suppose the go to tool for fitting non-linear models in R is nls of the stats package. In this post I will show an alternative approach with Stan/RStan, as illustrated in the example, Dugongs: ‘nonlinear growth curve’, that is part of Stan’s documentation.

13 Tips to make you awesome in Data Science / Analytics Jobs

1. Understand the business before you start solving problems
2. Think hard of whether you are solving an underlying problem or just an outcome
3. Spend more time on finding out the right evaluation metric and how much is required for implementation
4. Follow the diverge-converge thinking process to avoid pre-mature convergence
5. Break industry silos to think of alternate solutions
6. Engage with business counterparts throughout the process
7. Think of simplest implementation levers to bring your idea to life
8. While making a business deck, make sure you lay it out in their language
9. Learn to speak business language while presenting to business leaders
10. Actively follow up on the implementation plan
11. Actively participate in Data Hackathons
12. Read blogs and books on upcoming tools and techniques on analytics
13. Learn upcoming tools to know what is possible and what is not

Amazon Mechanical Turk: help for building your Machine Learning datasets

How to use Mechanical Turk in combination with Amazon ML for dataset labelling

Book Comment: Think Bayes

In conclusion, this is a very original introduction to Bayesian analysis, which I welcome for the reasons above. Of course, it is only an introduction, which should be followed by a deeper entry into the topic, and with [more] maths. In order to handle more realistic models and datasets.

Halloween: An Excuse for Plotting with Icons

In my course on the GLM, we are discussing residual plots this week. Given that it is also Halloween this Saturday, it seems like a perfect time to code up a residual plot made of ghosts.