Category: Machine Learning

  • More Sankey for Less Confusion?

    More Sankey for Less Confusion?

    Confusion Matrixes are essential for evaluating classifiers, but for some who are new to them, they can cause, well, confusion. Sankey Diagrams are an alternative way of representing matrix data, and I’ve found some people – who are new to matrix data, like business domain experts who are not experienced data scientists – find them…

  • Melbourne Data Visualisation Meetup – October 2020

    Melbourne Data Visualisation Meetup – October 2020

    I presented at the Melbourne Data Visualisation Meetup along with Ned Letcher, who gave an awesome overview of Python Libraries for Building Data Apps (an analytics superpower). The topic was Data Visualisation – Good for Business. Data Visualisation is key for gaining new knowledge, better engaging audiences, and driving meaningful action. We’ll share bespoke data…

  • Applying Software Engineering Practices to Data Science

    Applying Software Engineering Practices to Data Science

    I had fun recording this podcast on Applying Software Engineering Practices to Data Science with Zhamak Dehghani, Mike Mason and Danilo Sato. The need for high quality information at speed has never been greater thanks to competition and the impact of the global pandemic. Here, our podcast team explores how data science is helping the…

  • The Lockdown Wheelie Project, Part 2

    The Lockdown Wheelie Project, Part 2

    I now have an AI coach for my wheelie project. Coach has seen over 1,500 of my wheelies, and reckons they can tell pretty quickly whether my effort will be wheelie good or bad. Coach also fits on my phone, so they come on rides when I want real-time advice. Read the full article over…

  • The Lockdown Wheelie Project

    The Lockdown Wheelie Project

    “It’s Strava for wheelies,” my lockdown project, combining hyper-local exercise with data analytics to track and guide improvement. Practising wheelies is a great way to stay positive; after all, it’s looking up, moving forward. Read the full write-up over on Medium at The Lockdown Wheelie Project.

  • Data in the New Normal

    Data in the New Normal

    I provided some commentary for this article in CMO magazine about how data could provide insight into changes in behaviour driven by responses to COVID-19.

  • Ticker TV Customers & Tech

    Ticker TV Customers & Tech

    In this live interview, I talked with Ticker TV about how organisations are using data to understand changes driven by responses to COVID-19.

  • ML Interpretability with Ambient Visualisations

    ML Interpretability with Ambient Visualisations

    I produced some ambient visualisations as background to short talks on the topic of Interpreting the Opaque Box of ML from ThoughtWorks Technology Radar Volume 21. The talks were presented in breaks at the YOW Developer Conference. Here are my speaker notes. Theme Intro The theme I’m talking about is Interpreting the Opaque Box of…

  • Cost Sensitive Learning – A Hitchhikers Guide

    Cost Sensitive Learning – A Hitchhikers Guide

    Typically prediction is about getting the right answer. But many prediction problems have large and asymmetric costs for different types of mistakes. And often, the chance of making mistakes is exacerbated by training data imbalances. Cost-Sensitive Learning is the range of techniques for extending standard ML approaches to deal with imbalanced data and outcomes. Cost-sensitive…

  • Continuous Intelligence at Thoughtworks Live

    Continuous Intelligence at Thoughtworks Live

    Mat Kelcey and I wrote on this talk together. Mat presented at the Sydney event (slides) and I presented at the Melbourne Event (different but same slides). We also had the pleasure of presenting alongside international guests Arif Wider and Sean Gustafson who shared their excellent DataDevOps manifesto (there’s a video from NDC too). I’d…