Dublin Data Science

 
 
 

Data visualisation in D3.JS – without the JavaScript

Details:
In this session, we will look at D3.JS – an incredibly powerful JavaScript library that can help us bring data to life for ourselves or for our stakeholders.

D3.JS is notoriously fiddly to get working – but, after a lot of trial and error, the speaker has created a method called “data cuckoo-ing” that lets us start playing around with D3.JS visualisations without needing to be able to code in JavaScript.

This session will introduce D3.JS, describe “data cuckoo-ing” and will discuss about ways we can use interactive visualisations to help ourselves to analyse data. It will also include a live demo where we the speaker will attempt to live code a D3.JS visualisation with some new data without using JavaScript.

Speaker:
Rudi O’Reilly Meehan, Director at Data and Design

About the speaker:
Rudi started off as a mechanical engineer before transitioning into data science, a decision he took after attending a Dublin data science meetup! He spent 3 years working in The Dock, Accenture’s global centre for innovation, where he was tasked with bringing dozens of clients’ data to life in new and interesting ways.

Recently, he has set up Data and Design, a company that combines data science, data visualisation and data storytelling to transform clients’ data so they can make better informed decisions for their business.

 
 
 

For 2022, we are starting a series of workshops to introduce the concept of Bayesian statistics using a practical real-world problem: building customer analytics models to help predict customer behaviour.

All code for my workshops and talks can be found in this GitHub repo:

https://github.com/kaybenleroll/data_workshops

This workshop is contained in the ws_clvbayes_202201/ folder

This series of workshops is done live, with code being commited and pushed to the above GitHub repository as well as the Dockerfile infrastructure to build the container to run the code.

Bayesian statistics is an approach that enables the combination of domain knowledge, data and statistical modelling in a principled and logical way. The primary outputs of these models are distributions of the model parameters that allows us to quantify the uncertainty in our models.

In the eighth workshop in this series we use the P/NBD model on real world data, discuss issues with sample validity, and show a few different approaches to diagnosing the problems and how we might alleviate these issues..

We strive to make our workshops as standalone as possible, so new attendees are always welcome!

This workshop will be broadcast using Zoom and will be recorded and made available online via our YouTube channel.