Conor

Conor McGregor is set to make his film acting debut opposite Jake Gyllenhaal in Road House.The film is a remake of the Eighties classic, and is being produced for Prime Video.The Bourne Identity’s Doug Liman is attached to direct the feature, which will see Gyllenhaal tackle the role first inhabited by Patrick Swayze in 1989’s Road House.In the film, Gyllenhaal plays a former UFC fighter who works as a bouncer at a seamy road house in the Florida Keys. Deadline reports that, while the exact details of McGregor’s role are…

Data exploration and knowledge generation using non-linear models(source: flaticon)Black-box/non-linear models can automatically model complex relationships in data. Capturing these relationships is what increases their accuracy compared to linear models. However, accurate predictions are only one of the benefits. We can analyse the black-box models to learn how they make those predictions. This can reveal underlying relationships in our dataset. In some cases, these can be completely new to us. In this way, machine…

My process, tools and tips for writing data science articlesPhoto by Christin Hume on UnsplashI find the blank page of every new article to be a bit daunting. There is so much work to be done. You need to do research, draft, edit and add graphics. In some cases, you will need to learn something completely new. Every writer will have some sort of process to help deal with this workload.My process started as a common checklist for every article. Breaking the article down step by step made the overall workload seem more…

The intuition, maths and code (R and Python) behind partial dependence plots and individual conditional expectation plots(source: author)Both PDPs and ICE plots can help us understand how our models make predictions. Using PDPs we can visualise the relationship between model features and the target variable. They can tell us if a relationship is linear, non-linear or if there is no relationship. Similarly, ICE Plots can be used when there are interactions between features. We will go into depth on these two methods.We…

Adding up SHAP values of categorical features that have been transformed with one-hot encodingsPhoto by Kalineri on UnsplashCategorical features need to be transformed before they can be used in a model. One-hot encoding is a common way to do this: We end up with a binary variable for each category. This is fine until it comes to understanding the model using SHAP. Every binary variable will have its own SHAP value. This makes it difficult to understand the overall contribution of the original categorical feature.A simple…

3 reasons why interpretable models are more likely to be fair(source: flaticon)Interpretability and fairness seem to go hand in hand. Interpretability involves understanding how models make predictions. Fairness involves understanding if predictions are biased towards certain groups. These characteristics are consistently mentioned together in responsible AI frameworks and ML conferences. However, interpretability does not necessarily imply fairness.That being said, an interpretable model is still more likely to be fair.…

Pre-processing, in-processing and post-processing quantitative approaches. As well as non-quantitative approaches: limit the use of ML, interpretability, explanations, address the root cause, awareness of the problem and team diversity(Source: flaticon)Fairness in machine learning is a complicated issue. To make matters worse, the people responsible for building models do not necessarily have the skills to ensure they are fair. This is because the reasons for unfairness go beyond data and algorithms. This means solutions…

How to explain your model in a human-friendly wayPhoto by Jason Goodman on UnsplashAn important part of a data scientist’s role is to explain model predictions. Often, the person receiving the explanation will be non-technical. If you start talking about cost functions, hyperparameters or p-values you will be met with blank stares. We need to translate these technical concepts into layman’s terms. This process can be more challenging than building the model itself.We will explore how you can give human-friendly…