/explore
|
You are here 
|
www.machinedlearnings.com | ||
| | | | |
zserge.com
|
|
| | | | | Neural network and deep learning introduction for those who skipped the math class but wants to follow the trend | |
| | | | |
www.paepper.com
|
|
| | | | | Recent advances in training deep neural networks have led to a whole bunch of impressive machine learning models which are able to tackle a very diverse range of tasks. When you are developing such a model, one of the notable downsides is that it is considered a "black-box" approach in the sense that your model learns from data you feed it, but you don't really know what is going on inside the model. | |
| | | | |
stribny.name
|
|
| | | | | Fields in Artificial Intelligence and what libraries to use to address them. | |
| | | | |
wtfleming.github.io
|
|
| | | [AI summary] This post discusses achieving 99.1% accuracy in binary image classification of cats and dogs using an ensemble of ResNet models with PyTorch. | ||
