This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have ...

By the end of this book, you’ll have learned to create graph datasets, implement graph neural networks using Python and PyTorch Geometric, and apply them to solve real-world problems, along with ...

The readers can learn how to train convolutional neural networks (CNNs), recurrent neural networks (RNNs), and extended short-term memory networks (LSTMs) in R using real-world projects ...

The intersection of neuroscience and artificial intelligence has seen remarkable progress, notably through the development of an open-source Python library known as “snnTorch.” This innovative code, ...

This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have ...