In this tutorial by Python Simplified, learn a very important computer science concept – number base conversion!
And more particularly – converting binary numbers to decimals and vice versa.
In this lesson from Python Simplified learn the binary Log Loss/Cross Entropy Error Function and break it down to the very basic details.
Have you ever wondered how computers perceive raster images?
In this video, Python Simplified shows you how to understand the math and structure behind digital pictures.
Fireship explains the fundamentals of Web Assembly in 100 Seconds and why it’s a big deal.
Yannic Kilcher explains the paper “Hopfield Networks is All You Need.”
Hopfield Networks are one of the classic models of biological memory networks. This paper generalizes modern Hopfield Networks to continuous states and shows that the corresponding update rule is equal to the attention mechanism used in modern Transformers. It further analyzes a pre-trained BERT model through the lens of Hopfield Networks and uses a Hopfield Attention Layer to perform Immune Repertoire Classification.
Content outline:
- 0:00 – Intro & Overview
- 1:35 – Binary Hopfield Networks
- 5:55 – Continuous Hopfield Networks
- 8:15 – Update Rules & Energy Functions
- 13:30 – Connection to Transformers
- 14:35 – Hopfield Attention Layers
- 26:45 – Theoretical Analysis
- 48:10 – Investigating BERT
- 1:02:30 – Immune Repertoire Classification