This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Abstract: With the advancement of technology, the field of multi-channel time series forecasting has emerged as a focal point of research. In this context, spatio-temporal graph neural networks have ...

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 ...

Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...

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 ...