Vision Language models: towards multi-modal deep learning
A review of state of the art vision-language models such as CLIP, DALLE, ALIGN and SimVL
Why multi-head self attention works: math, intuitions and 10+1 hidden insights
Learn everything there is to know about the attention mechanisms of the infamous transformer, through 10+1 hidden insights and observations
How Positional Embeddings work in Self-Attention (code in Pytorch)
Understand how positional embeddings emerged and how we use the inside self-attention to model highly structured data such as images
How Transformers work in deep learning and NLP: an intuitive introduction
An intuitive understanding on Transformers and how they are used in Machine Translation. After analyzing all subcomponents one by one such as self-attention and positional encodings , we explain the principles behind the Encoder and Decoder and why Transformers work so well
How Attention works in Deep Learning: understanding the attention mechanism in sequence models
New to Natural Language Processing? This is the ultimate beginner’s guide to the attention mechanism and sequence learning to get you started
Document clustering
Use unsupervised learning to cluster documents based on their content