A step-by-step tutorial on ways to incorporate CNNs for time-series data — My first-ever publication on Medium was a deep dive into convolutional neural networks (CNN). In that post, I went through a step-by-step example on how to use this technique for medical image classification. It’s a powerful tool in the arsenal of any dataphile, and it’s important to recognize the CNN…

In a world quick to silence, this is a father’s heartfelt manifesto to make sure children’s voices are being heard — The line separating good and evil passes not through states, nor between classes, nor between political parties either — but right through every human heart — and through all human hearts. This line shifts. Inside us it oscillates with the years. …

Comparing DeepHit and DeepSurv models — In my last post, I walked through examples using Random Forest, Gradient Boosted, and SVM survival models. Today, I will show you how you can approach the same type of problems using deep neural networks. …

A step-by-step tutorial with examples — In this post we will compare several advanced methods to approach time-to-event analyses (aka Survival analyses). Specifically, we will cover Random Forest, Gradient Boosted and SVM survival models. Time-to-event analyses are important methods to help us analyze problems where there is a temporal component to our research question. …

In this post, I will walk you through an example using Google’s TabNet for a classification problem. Despite the recent explosion of Deep Neural Nets (DNNs) for image, audio, and text, it seems like tasks using good ol’ structured tabular data have been somewhat ignored. While it’s true that much…

Leveraging the power of BERT sentence embeddings using Spark NLP — In a previous post, I demonstrated how different word embeddings (GloVe, ELMo, BERT) could be used for a text classification task. We saw how (and why) capturing context was important to maximize accuracy. We also explored several ways text can be preprocessed to improve results. …

A guide to state-of-the-art text classification using Spark NLP — One of the most challenging tasks for machine learning models is finding the best way to to generate numeric representations for words so the model can use that information in its calculations. In computer vision tasks, the red channel in a color (RGB) image will always refer to the red…

A simple approach to gain insight into the limitations of your CNN model — There is something magical about the way modern algorithms solve our current data-driven problems. Despite coming from a neuroscience background with a strong understanding of our sensory systems, I feel humbled when I write algorithms that mimic them. One things that strikes me most, however, is the fact that both…

How to appropriately measure bivariate relationships in your data — Valentine’s Day may be a distant memory, yet it still feels like the perfect opportunity to discuss relationships with you — That is relationships within your data. By the end of this post, you will have a better understanding of the most common correlation coefficients and when to use them…