A couple of weeks ago, I started working with survival analysis. It was fairly new to me, so I had to dig into some new methods. There was one method that captured my attention: random survival forests (RSFs). It’s one of many statistical learning techniques designed to work with right-censored… Read More »Dealing with right-censored data in machine learning: Random Survival Forests
In this blog post I explain how to create a DataGenerator with a one-hot encoder to encode your labels in the same way for every batch. Some months ago, I tried training a text generator on a huge corpus of text with an LSTM model. Basically, it’s a model that… Read More »One-hot encoding with a TensorFlow DataGenerator
Toen Roger McNamee in maart 2019 in zijn podcast-interview met Sam Harris verkondigde dat Android, het mobiele besturingssysteemvan Google, een stofzuiger is voor jouw data, had hij niet kunnen voorzien wat 2 maand later op Google IO aangekondigd zou worden: federated learning. Binnenkort moet de tech-gigant jouw data niet meer… Read More »Federated Learning: Een einde aan het privacydebat?
In this blog post I will introduce you to building and training your own neural network algorithm in R through Keras & TensorFlow. If you haven’t installed Keras for R yet, please follow the instructions explained in part 1. I have explicitly chosen to work with structured data in this… Read More »Using Keras in R: Training a model
Personally, Random Forest is one of my favorite algorithms for supervised learning. It’s quick and dirty and still allows for some interpretation. However, R and the RandomForest package are somewhat cryptic when it comes to requirements not met to properly train the algorithm. I bumped a lot into this error… Read More »randomForest gives NA/NaN/Inf in foreign function call and how to solve it