Deep Learning with Yacine on MSN

Adadelta optimizer explained – Python tutorial for beginners & pros

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind Adadelta, why it was introduced as an improvement over Adagrad, and guides you ...

Not all MMM tools are equal: Meridian, Robyn, Orbit, and Prophet explained

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
Deep Learning with Yacine on MSN

Nadam optimizer explained: Python tutorial for beginners & pros

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, explains how it builds on Adam with Nesterov momentum, and shows you how to ...
IEEE

Spectral Bayesian Optimization Using a Physics-Informed Rational Szegö Kernel for Microwave Design

Abstract: Microwave device design increasingly relies on surrogate modeling to accelerate optimization and reduce costly electromagnetic (EM) simulations. This article presents a spectral Bayesian ...
IEEE

Controller Adaptation via Learning Solutions of Contextual Bayesian Optimization

Abstract: In this work, we propose a framework for adapting the controller's parameters based on learning optimal solutions from contextual black-box optimization problems. We consider a class of ...
GitHub

Deep Learning Model Optimization and Tuning

A comprehensive tutorial repository for learning deep learning model optimization techniques, including network tuning, backpropagation optimization, overfitting management, and root cause analysis.