Explore >> Select a destination
|
You are here 
|
blog.georgeshakan.com | ||
| | | | |
hadrienj.github.io
|
|
| | | | | In this post, we will learn about the Moore Penrose pseudoinverse as a way to find an approaching solution where no solution exists. In some cases, a system ... | |
| | | | |
comsci.blog
|
|
| | | | | In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture. | |
| | | | |
grigory.github.io
|
|
| | | | | Discussion of the class on Foundations of Data Science that I am teaching at IU this Fall. | |
| | | | |
scorpil.com
|
|
| | | In Part One of the "Understanding Generative AI" series, we delved into Tokenization - the process of dividing text into tokens, which serve as the fundamental units of information for neural networks. These tokens are crucial in shaping how AI interprets and processes language. Building upon this foundational knowledge, we are now ready to explore Neural Networks - the cornerstone technology underpinning all Artificial Intelligence research. A Short Look into the History Neural Networks, as a technology, have their roots in the 1940s and 1950s. | ||
