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 ...

Abstract: Untrained neural network (UNN) has shown promising potential for solving inverse scattering problems (ISPs) with high flexibility and no need of training data. However, iterative ...

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and other biological networks look the way they do. The prevailing theory held ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

This system uses a neural network to predict NBA game outcomes and total points, with integrated betting strategy tools including Expected Value calculation and Kelly Criterion bet sizing.

CATS-Net (Concept Abstraction and Task-Solving Network) is a comprehensive framework for understanding and implementing concept abstraction in neural networks. The system combines supervised learning ...

French telecommunications operator Free has joined Nokia’s Network as Code API ecosystem, making it easier for developers and enterprises to build, test and deploy new applications that securely tap ...

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 ...

Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...