Autoencoder are a type of model that are trained by recontructing an output identical to the input after reducing it to lower dimensions inside the model. That lower dimension vector is called latent ...

This post is a continuation of my previous post Extreme Rare Event Classification using Autoencoders. In the previous post, we talked about the challenges in an extremely rare event data with less ...

All the tutorials about TensorFlow and neural networks I have shared until now have been about supervised learning. This one will be about the Autoenocder which is an unsupervised learning technique.

Anomaly detection, also called outlier detection, is the process of finding rare items in a dataset. Examples include finding fraudulent login events and fake news items. Take a look at the demo ...