Using Talos for Feature Hyperparameter Optimization?

When designing the architecture for an artificial neural network, there exist a variety of parameters that can be tuned. It is indeed an art in itself to find the right combination for these parameters to achieve the highest accuracy. In this blog post, we are testing the usage of Talos for hyperparameter optimization of a neural network.

Loss and accuracy diagrams

Predicting Credit Card Fraud with Unsupervised Learning

In previous blog post about Credit Card Fraud we used an artificial neural network for predicting whether a given transaction is fraudulent, with great results. However, sometimes in problems like these, where we naturally have an imbalanced distribution in our dataset, we might not always have collected data for the minority of the outcomes, in this case, the fraudulent transactions.

Novelty detecion