Category Archives: Transformers

The goal of a machine learning regression problem is to predict a single numeric value. Classical ML regression techniques include linear regression, kernel ridge regression, gradient boosting regression, and others. I’ve been experimenting with a new algorithm for machine learning … Continue reading →

I’ve been looking at adding a Transformer module to a PyTorch regression network. Because the key functionality of a Transformer is the attention mechanism, I’ve also been looking at adding a custom Attention module instead of a Transformer. There are … Continue reading →

I’ve been looking at adding a Transformer module to a PyTorch regression network. Because the key functionality of a Transformer is the attention mechanism, I’ve also been looking at adding a custom Attention module instead of a Transformer. There are … Continue reading →

I’ve been looking at adding a Transformer module to a PyTorch regression network. Because the key functionality of a Transformer is the attention mechanism, I’ve also been looking at adding a custom Attention module instead of a Transformer. There are … Continue reading →

I’ve been looking at adding a Transformer module to a PyTorch regression network. Because the key functionality of a Transformer is the attention mechanism, I’ve also been looking at adding a custom Attention module instead of a Transformer. There are … Continue reading →

I’ve been looking at adding a Transformer module to a PyTorch regression network. Because the key functionality of a Transformer is the attention mechanism, I’ve also been looking at adding a custom Attention module instead of a Transformer. For both … Continue reading →

Whew! This may be one of the worst blog titles I’ve ever written, but it was the best I could do. Let me try to explain. The idea starts with the data. Most ordinary data is not sequential. For example, … Continue reading →

The goal of one of my ongoing projects is to find anomalies in medical data, where the data is ordered in some way. I imagine each line of data represents a hospital patient, and each value on a line is … Continue reading →

The goal of a machine learning regression problem is to predict a single numeric value. Classical ML regression techniques include linear regression, Gaussian process regression, gradient boosting regression, and others. I’ve been experimenting with a new algorithm for machine learning … Continue reading →