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20 posts

Beginners Guide To Transformer Models

In our previous post, we presented an introduction to Seq2Seq models – models that take a sequence as an input and produce a sequence for their output. Back in 2014, they revolutionized the field of Natural Language Processing (NLP), especially in translation…

Understanding Seq2Seq Models

Most of the machine learning applications you’ve likely heard about are concerned with processing data such as images or databases – their key characteristic being that they can be “taken in” by a learning model all at once. They don’t have any temporal…

The Intuition Behind Variational Autoencoders

When reading about Machine Learning, the majority of the material you’ve encountered is likely concerned with classification problems. You have a certain input, and the ML model tries to figure out the features of that input. For example, a classification model can decide…