Talks and Workshops

Standard

I enjoy giving talks and workshops on Data Analytics. Here is a list of some of the talks I’ve given. In my Mathematics master I regularly gave talks on technical topics, and previously I worked as a Tutor and Technician in a School in Northern Ireland. I consider the evangelism of data and analytics to be an important part of my job as a professional data scientist!

Upcoming

I’m giving a tutorial called ‘Lies damned lies and statistics’ at PyData London 2016. I’ll be discussing different statistical and machine learning approaches to the same kinds of problems. The aim will be to help those who know either Bayesian statistics or Machine Learning bridge the gap to others.

Slides and Videos from Past Events

In April 2016 I gave an invited talk at the Toulouse Data Science meetup which was a slightly adjusted version of  Map of the Stack‘.

At PyData Amsterdam in March 2016- I gave the second Keynote on a ‘Map of the Stack‘.

PyCon Ireland From the Lab to the Factory (Dublin, Ireland October 2015) – I gave a talk on the business side of delivering data products – a trope I used was it is like ‘going from the lab to the factory’. This was a well-received talk based on the feedback and I gave my audience a collection of tools they could use to solve these challenges.

EuroSciPy 2015 (Cambridge, England Summer 2015): I gave a talk on Probabilistic Programming applied to Sports Analytics – slides are here.

My PyData London tutorial was an extended version of the above talk.

I spoke at PyData in Berlin.
The link is here

The blurb for my PyData Berlin talk is mentioned here.
Abstract: “Probabilistic Programming and Bayesian Methods are called by some a new paradigm. There are numerous interesting applications such as to Quantitative Finance.
I’ll discuss what probabilistic programming is, why should you care and how to use PyMC and PyMC3 from Python to implement these methods. I’ll be applying these methods to studying the problem of ‘rugby sports analytics’ particularly how to model the winning team in the recent Six Nations in Rugby. I will discuss the framework and how I was able to quickly and easily produce an innovative and powerful model as a non-expert.”

In May 2015 I gave a preview of my PyData Talk in Berlin at the Data Science Meetup in Luxembourg on ‘Probabilistic Programming and Rugby Analytics‘ – where I presented a case study and introduction to Bayesian Statistics to a technical audience. My case study was the problem of ‘how to predict the winner of the Six Nations’. I used the PyMC library in Python to build up statistical models as part of the Probabilistic Programming paradigm. This was based on my popular Blog Post which I later submitted to the acclaimed open source textbook Probabilistic Programming and Bayesian Methods for Hackers. I gave this talk using an IPython notebook, which proved to be a great method for presenting this technical material.

In October 2014 I gave a talk at Impactory in Luxembourg – a co-working space and Tech Accelerator. This was an introductory talk to a business audience about ‘Data Science and your business‘. I talked about my experience at different small firms, and large firms and the opportunities for Data Science in various industries.

In October 2014 I also gave a talk at the Data Science Meetup in Luxembourg. This was on ‘Data Science Models in Production‘ discussing my work with a small company on developing a mathematical modelling engine that was the backbone of a ‘data product’. This talk was highly successful and I gave a version of this talk at PyCon Italy – held in Florence – in April 2015. The aim of this talk was to explain what a ‘data product’ was, and discuss some of the challenges of getting data science models into production code. I also talked about the tool choices I made in my own case study. It was well-received, high level and got a great response from the audience. Edit: Those interested can see my video here, it was a really interesting talk to give, and the questions were fascinating.

When I was a freelance consultant in the Benelux I gave a private 5 minute talk on Data Science in the Game industry. Here are the slides. – This is from July 2014

My Mathematical research and talks as a Masters student are all here. I specialized in Statistics and Concentration of Measure. It was from this research that I became interested in Machine Learning and Bayesian Models.

Thesis

My Masters Thesis on ‘Concentration Inequalities and some applications to Statistical Learning Theory‘ is an introduction to the world of Concentration of Measure, VC Theory and I used this to apply to understanding the generalization error of Econometric Forecasting Models.

Talk: Can Probabilistic Programming be applied to Rugby?

Standard

Yesterday evening I gave a talk at the Data Science Meetup in Luxembourg.

This is part of my preparation for the talk at PyData the Python conference for Data Enthusiasts in Berlin.

A few remarks – my slides from last night are here in IPython notebook format.

I used for the presentation the excellent RISE library from https://twitter.com/damian_avila this easily converts IPython notebooks into Reveal JS format and I really recommend it.

Abstract of my Talk: Probabilistic Programming and Bayesian Methods are called by some a new paradigm. There are numerous interesting applications such as to Quantitative Finance.
I’ll discuss what probabilistic programming is, why should you care and how to use PyMC from Python to implement these methods. I’ll be applying these methods to studying the problem of ‘rugby sports analytics’ particularly how to model the winning team in the recent Six Nations in Rugby. I will discuss the framework and how I was able to quickly and easily produce an innovative and powerful model as a non-expert.

The talk also serves as a useful example of Probabilistic Programming, why it is useful and how to use PyMC to model an event rather than say a domain specific language like STAN.

On Academic talks

Link

On Academic talks

Cosma Shalizi, has an excellent talk on Academic talks.

I suggest one reads it.

I merely quote my favourite part:

  1. 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.
  2. 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?”.
  3. 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.