This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

Have you ever wondered how some of the most complex AI models or data-driven insights are built without requiring a supercomputer or expensive software? Enter Google Colab, a platform that has become ...

Despite its small stature, the city of Keene, has become an example of the safety and climate benefits of swapping traffic lights for roundabouts. Credit... Supported by By Sachi Kitajima Mulkey ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...

python scripts/bayesian_train.py --config [list of paths to configs to be merged, rightmost will override values of previous ones] Example: scripts/bayesian_train.py ...

Abstract: The practice of deep learning has shown that neural networks generalize remarkably well even with an extreme number of learned parameters. This appears to contradict traditional statistical ...

Our brain’s memory center bears a sleek design. A peek into living tissue from human hippocampi, a brain region crucial for memory and learning, revealed relatively few cell-to-cell connections for ...