Explore >> Select a destination
|
You are here 
|
felixlaumon.github.io | ||
| | | | |
michael-lewis.com
|
|
| | | | | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background. | |
| | | | |
machinethink.net
|
|
| | | | | An in-depth look at how fast object detection models are trained | |
| | | | |
www.v7labs.com
|
|
| | | | | Learn about the different types of neural network architectures. | |
| | | | |
blog.paperspace.com
|
|
| | | Follow this tutorial to learn what attention in deep learning is, and why attention is so important in image classification tasks. We then follow up with a demo on implementing attention from scratch with VGG. | ||
