One of the distinctions I like to make about modern ‘Data Science’ is between ‘data science for decision support’ and ‘machine learning’. h Basically speaking machine learning, which is often product-focused – is generally something like ‘there’s this problem in fraud, credit scoring’ and we need an automated and deployed system. You’ll often work super… Continue reading Data Science for Decision Support: Or why Bayesian Analysis matters
(Linkedin picture) I was very happy to interview Natalie about her data science stuff – as she gave a really cool Machine Learning focused talk at PyData in London this year, which was full of insights into the challenges of doing Machine Learning with Imbalanced data sets. Natalie leads the data team at GoCardless, a… Continue reading Interview with a Data Scientist: Nathalie Hockham
As part of my ongoing series with interviews with Data Scientists and Data Analysts, I provide an interview with Ignacio Elola, who is the data scientist at Import.io. Import.io is a cool web platform for allowing you easier access to web data and is one of the cool data scientist enabling tools we see on… Continue reading Interview with a Data Scientist: Ignacio Elola
J.D.Long is the current AVP Risk Management at RenaissanceRe and has a 15 year history of working as an analytics professional. I sent him an interview recently to see what he would say. Good questions Peadar. Here’s a really fast attempt at answers: 1. What project have you worked on do you wish you could go back… Continue reading An interview with a data artisan
Cosma Shalizi, has an excellent talk on Academic talks.
I suggest one reads it.
I merely quote my favourite part:
- The point of the talk is not to please you, by reminding yourself of what a badass you are, but to tell your audience something useful and interesting. (Note to graduate students: It is important that you internalize that you are, in fact, a badass, but it is also important that then you move on. Needing to have your ego stroked by random academics listening to talks is a sign that you have not yet reached this stage.) Unless something matters to your actual message, it really doesn’t belong in the main body of the talk.
- You can stick an arbitrary amount of detail in the “I’m glad you asked that” slides, which go after the one which says “Thank you for your attention! Any questions?”.
- You also can and should put all these details in your paper, and the people who really care, to whom it really matters, will go read your paper. Once again, think of an academic talk as an extended oral abstract.
Internalise that you are in fact a bad ass. I wish more Professors gave advice like that.